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Hello everyone and welcome back to the SourceForge podcast.
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I'm your host, Bo Hamilton, and today we are looking at a problem that affects nearly every business with employees working outside the office.
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So think about a technician who notices a machine starting to fail, or an inspector who finds a safety issue, or maybe a crew that documents damage at a job site.
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All that information can be valuable and time sensitive, of course, but it often gets buried in a form, maybe emailed as a PDF or entered into a spreadsheet that no one reviews until days later.
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And by the time it reaches the person who can act on it, the opportunity may already be gone, right?
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The crew has moved on.
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Maybe another truck has to be sent out or an invoice gets delayed, or maybe even like just a small problem becomes a much more expensive one, right?
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That's that's sort of the issue we're trying to convey here.
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And many companies have already replaced paper forms with apps, but collecting information digitally is only just part of the solution.
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The bigger challenge is turning that information into a decision while it still matters.
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And that is what FastField is designed to do, part of QuickBase.
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FastField helps teams collect information from job sites, think uh plant floors and vehicles and other field environments, and then immediately route it to the right people and the right business systems.
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And its newer AI capabilities can even review job site photos for potential safety, compliance, and equipment issues.
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So joining me to explain how all it works is Ross Marshall, Senior Director of Growth Operations and Finance at FastField.
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Uh, Ross, I'm really excited to get into this discussion and learn more about what it is you're doing over at FastField.
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So um I'm I'm really happy to have you here.
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Welcome to the podcast.
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Thanks for having me, Bo.
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Um now I want to start at the beginning, start with some of the basics here for listeners and viewers who might not be familiar with uh FastField.
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For anyone who hasn't come across FastField before, how would you describe what it does?
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So, what is FastField?
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At its core, FastField is a field data collection software.
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It is for individuals, whether they're out in the field, on a manufacturing floor, um, who need to collect data.
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And going beyond that, it's not simply just the act of turning paper into a digitized form.
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It is, it is what do you do with that data?
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It turns that data into something structured, something that can be routed that is visible to the back office.
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So it's really that connective tissue between the individuals out in the field, the back office.
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It it helps the whole workflow of a field team.
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Okay, the connective tissue.
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I like that um descriptor.
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Um I know I know a lot of teams figure they've already sort of handled a lot of these um these issues with their own sort of patchwork um solutions.
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Um they ditch the clipboards, maybe they've got an app or some sort of basic forums, but where does that usually fall apart?
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And then like what's what's it costing to them that they they don't even see or really take into account?
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Right.
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I I think to answer that question bluntly, it's the individual is not getting that report in a week or with three different spreadsheets.
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They are getting it instantaneously.
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It is a structured system.
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Um, the individual who sets it up, they set up the guardrails, they set up the parameters of of what we want.
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An individual is out there putting together an instant checklist.
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And when that form is filled out and it is submitted, there could be triggers, there could be um alerts that go off, and and the team is working together on that versus just a very plain, basic digital form is you are just digitizing information.
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There's there's nothing behind that.
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And so that's really the difference between our software and just filling out a digitized form.
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Um so I know there's a there's there's a real difference between uh you know a team that's let's say collecting field data and a team that's actually doing something with it.
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Um what does that that gap look like on a day-to-day basis?
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And then like what has to sort of change operationally to close that gap?
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I think it is it is putting together a digital process.
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It's it's not the illusion of a digital process.
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It is the individuals are out doing something.
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What is the downstream impact of that data, right?
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Is it we are looking, we are looking for, you know, audits of of trucks.
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And, you know, if there's a certain amount that that don't pass this, it flags for, you know, repair technician to to go out there versus having a bunch of information kind of siloed in an inbox or into a Excel spreadsheet that ultimately someone needs to ten key in that information and then review that information.
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It is the ability for those teams to work harmoniously together.
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And then the next step after that is to to get those work orders out, to get those, you know, those other job orders starting sooner than later.
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Yeah.
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So it sounds like it's it's the a lot of the bottleneck is really just it filters down to you know, a person just forgetting um to check on certain information or follow up.
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Um it's just uh it whittles down to a person remembering to check on the thing they're supposed to check on.
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Um and if you're building something that uh, you know, like a safety program, the issues there can really um start to unfold in uh unintended ways and the ways that you don't want to happen.
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Um walk me through what happens like the second someone hits submit on a form.
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Like where does that where does that data go?
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Uh, who sees it?
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How does it get to the right person to act on it?
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Depending on the rules that that you set up, once you hit submit, it can go to an inbox, it can go to the cloud, straight to an ERP, CCMS, SQL Server.
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Um one field event becomes a back office record, a notification, a trigger task to be done.
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And so it really depends on on how you set that up, but um, these forms are embedded in your tablet, phone, what whatever else you're bringing out into the field.
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And so there's there's a whole workflow behind it.
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Um the beautiful thing about Fast Field is it it works offline.
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So if you are out on an oil rig or you're you know four or five stories below ground in a basement, you can still do your work.
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You can still have all of the information that you need in front of you, be able to query it and um complete your tasks and submit.
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Once you get connectivity again, then those reports go you know through their normal workflows.
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So just because you are out of connectivity doesn't mean that you you have to go back to paper or that things aren't working.
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So it's a it's a it's a fantastic feature that we've had for for quite some time now.
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Yeah, okay.
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I was gonna ask about like what happens, you know, when you're you're working out in the middle of nowhere, there's no signal, no service, you know, the the um Starlink isn't connecting, or you're underground, um, you have that offline access.
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How long has that been a feature, been a part of the system?
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It it has been around.
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I I joined in 2019 and it was it was around then, so we've had it for quite some time, and it's it's really the differentiator between individuals looking at, okay, I need to move from paper to digitizing a form, but what's really behind that?
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Can you go out in the field and and continue to do your your day-to-day with with just you know a basic fields and and lists name, right?
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There's there's certainly more behind that.
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And once you get back to connectivity, you know, what's what's really the process there?
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Does it does it sync?
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You know, can can you receive new information?
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So that's where FastFuel, it's all interconnected and and and it helps people, you know, whether they're online or offline, can continue to do their day job.
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Yeah, it seems like it seems like one of those features that um it's almost like a boring feature, but it has like a really real-world like tangible use case, um, especially when you talk about those oil refinery rigs or you know, some underground operations.
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Um, and then it's also one of those features that's increasingly harder to come by, having offline support in today's world where you're constantly, you know, sending data up to the cloud and and uh using AI to run on multiple like uh cloud-based remote servers.
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Um you don't really see offline support um as much nowadays with with our sort of various services we all use and love and whatnot.
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So um that is pretty exciting.
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And uh it's again, like you're you're uh the offline piece, it doesn't sound particularly exciting until you're you're in a basement or like a substation or something like that.
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Right.
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It it's it's certainly an exciting feature for individuals who are out in the field.
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You know, for for you and I, possibly sitting in an office all day, it is um it it it seems like table stakes, but to be out, you know, on an oil rig or you know, servicing, you know, a substation, it it is, it's it's a game changer.
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It it changes the way that people can can do their day-to-day.
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And um, you know, I have a a great anecdotal example.
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I was at a uh a pizza parlor about a week ago with my son for his baseball team, and three individuals walked up.
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They had a black polo.
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I I won't share the logo, but they tapped me on the shoulder and I was a bit startled, and and the guy, you know, extended his hand and I shook it, and he's like, You work at Fastfield?
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And I go, I do work at Fastfield, I've been there for about six years.
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He goes, You guys have changed, has fundamentally changed the way that we work on a day-to-day basis.
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We're we're out in the field servicing fences and and electrical, you know, boxes, and you fundamentally have changed the way that we do things.
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And you have saved us each 20, 30 hours a week.
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And there was there's three of them.
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It's just like, you know, those types of stories, they they make you feel good.
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And I kind of like, you know, walked away from that and was just like, that that was a fantastic out-of-the-blue scenario, but um just an example of how how offline capabilities, you know, help help people shave 20, 30 hours off their work week.
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So you've I wanted to get into the AI aspect, because of course you have AI workflows built into the platform.
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What does that look like in the real world?
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Like how's it sort of how's it flagging problems?
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How's it routing things to the right people, servicing stuff that would otherwise just sort of like, you know, be buried in a spreadsheet or someone's inbox?
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Right.
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It it's really the difference between an inbox someone has to triage and a system that triages itself.
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It's it's making real-time decisions based off of guardrails that an individual sets up, but it's it's really, you know, flagging anomalies, prioritizing urgent items, you know, catching missing data within forms.
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And so it is, it's it's like that ride-along co-pilot for for you as a manager or an operator to to make sure that everybody out in the field you know is kind of within these boxes.
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You can imagine in highly regulated environments, it's it's not important, it's imperative to have something like this, to make sure things aren't missed, that thing, things are absolutely structured the way that they should be.
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So it's it's a fantastic feature that that helps reduce various types of um you know data inconsistencies or having to go back and rework it, or or well, these four fields aren't filled out towards the bottom.
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What happened here?
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Well, I need to go back to the job site and and reinspect because you know I forgot it at that point versus having a feature that flags it while you're there.
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You can't submit until until this is done.
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So it cuts down on time, cuts down on cost, um, it helps everybody.
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Yeah, I don't think it could be overstated just how you know helpful, like just relatively simple things like like really effective reminders um and and um like uh summarization of like dense information.
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And then if you're able to have some of these AIs and maybe agentic capabilities act like take on small repetitive tasks on a user's behalf.
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Um, yeah, I I'd be curious to like could learn more and hear more about like the um some of the specific features that the um you have built in in regards to what AI is doing here.
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Have you guys uh incorporated a lot of like agentic features?
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We we have, I think um some of the the biggest ones that I could point out would be our AI photo insights, where you can, you know, walk around a work site with your phone and and just capture uh a truck and it will it'll look at the image, it'll read it, and it'll start describing it to you.
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You know, the the front left tire has has wear and tear on the you know top left section of it.
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Or you're um a great real real world example I dealt with last week was uh an HVAC servicer.
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They're going around and you know, taking the tablet and looking at an HVAC unit.
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Um, top left-hand corner, there's corroded wires, which you know is is leading to possible, you know, burn scarring right there.
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Um the the housing unit of the HVAC, you know, there's screws that are loose, so it's it's open to the elements, things like that.
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It is describing it, it's rating it, and then it's providing essentially an incident report so that if you don't have something structured, it can it can create that for you, and it's it's cutting down on an inspection to two minutes rather than an hour, right?
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So it's a a fantastic feature that we recently launched, um, not three months ago.
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And it it has amazing real-world applications.
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Um, another great example would be just going through manufacturing floors.
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You can imagine, especially with uh a gigantic piece of machinery, the the amount of detail that can possibly be on that.
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Um, but taking a tablet or a phone and and just slowly just capturing it as as a video and and the AI analyzing the entire piece and and producing you know an incident report or an inspection report on something like that.
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It's it cuts down to minutes, what what could take an hour plus.
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So the the future is now truly with with how fast things are moving, you know, where we were five years ago, uh being just kind of basic data collection with with these few add-on features, and now we're starting to progress into um having these types of co-pilots ride with you in in your day-to-day to cut down your processes, you know, two minutes.
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Um obviously there's always the human element behind it, right?
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AI is not going to be the person that goes out there and and does everything.
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There are experts that are gonna go out there, use these tools to collect data rapidly, and then be able to use their experience, their judgment calls to say, you know, look, all of this looks great.
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This piece over here, I'm gonna annotate a little bit differently.
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You know, I see something over here that might not be right, so I'm gonna go and, you know, take a picture myself and submit it and write my own notes.
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But it it's it's that that co-pilot that really just kind of gives you a superpower out in the field.
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Um moving on to the next piece that that we we want to talk about is what we are releasing in August for for everybody is a true vibe coding platform for building a form.
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Um sometimes a barrier to entry for for anybody moving off paper is learning a new system, being able to go in and learn that tool.
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You know, do I have to have an expert who knows this tool?
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I always believe that Fast Field, the technology bar was quite low for us to be able to get in there, get your hands dirty, and build out a form.
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I believe, you know, what we're releasing in August, you just go in there and you do a very simple language prompt of what you want as a form and and what you need it to solve, and it will produce it for you within seconds.
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Within a matter of minutes, you are starting to build out an entire workflow for your operation.
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So I believe we've moved the bar down to our shoelaces, and anybody and everybody can start a trial with Fastfield and and be up and running within minutes.
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Um, it's a great time to be alive, and it is amazing to see the power of these kind of agentic systems.
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Not to not to date this podcast, but so it's probably already out uh for listeners and viewers.
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Um that is I I want to ask you, uh I want to get more into um unraveling, kind of some unpacking some of the features here with this platform and the AI specific features.
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You mentioned one thing that that caught my ear was um you mentioned the incident reporting in some of the examples.
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And I I want to talk about some of the high-stakes use cases like uh surrounding like safety and compliance, um, where a data gap can really sort of be a big a big issue that really bites and causes some real problems if if um things go missing.
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Um how do you how do you help teams get out of a reactive sort of incident reporting and into something a bit more proactive?
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And then like what does that shift sort of look like on the ground in the in the real world?
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You took the words right out of my mouth.
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What we always say is, you know, reactive incident reporting becomes a proactive system.
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And it is it's allowing companies to have a validation system that that happens at time of capture, not after, right?
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It's it is immediately while someone is there, while while the action is happening versus inputting in data and then five business days later that we we realize that you know we have um a machine who has tripped this many times and it's above our KPI threshold.
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And so it's it it breaks down on the time of you know safety and compliance and and how we support people, you know, be more buttoned up with their safety and compliance.
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Okay.
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And then you mentioned obviously the the photo insights uh part of the platform, AI looking at photos from the field in real time and and catching all sorts of like compliance issues uh before a person even sort of sort of like opens them up.
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Um I want to I want to like have you unravel that some more.
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Like how does that work?
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Um you mentioned you just hold up the tablet and just kind of scan the problem area, the area you want to find out, you know, learn learn more information about.
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Um and then yeah, what is it, what does it just change about inspections and quality workflows when AI is kind of taking that first pass?
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Instead of data dumping into a folder, you know, 150 uncategorized photos, it is returning structured findings based off of a photo, uh, a selection of photos, a video.
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It's identifying defects, hazards, very basic observations.
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And so it's it's putting together just a structured format versus having, again, you know, 150 uncategorized photos.
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It's it's giving you a severity rating, a confidence score.
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It's it's allowing you to really up-level your safety and compliance, incident reporting, you you name it.
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It's it's it's cutting down on all these individual steps that that companies deal with on a day-to-day basis.
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Do you uh how do you deal with the the false positives aspect?
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Um, because I imagine like, you know, AI is not is not perfect.
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Um, there's always going to be a little bit of like uh some issues, and that's that's why you kind of need a human in the loop to review things.
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Um but uh how do you, yeah, how have you sort of factored in that um sort of potential there with with false positives and some images?
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Human judgment always stays in the loop.
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You said it.
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It it is before I submit this form, just because this photo is filling out this form, it's giving me loads worth of data, it's going through and and and validating that that it is all correct.
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Um a a digital form that could have taken you 30, 40 minutes to fill out now takes you, you know, two, three minutes to fill out.
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But there's still that level of of human judgment um to go through there, make sure that that that everything is not only correct, but that it is you know structured in the way that it's not going to fire off an incident report because you know it's it's making it's making a wrong assumption, right?
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We're trying to um say that that this part of the equipment is is faulty when it's tying it back to a different part.
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And so there's always that human element um before submitting, you know, no different than using any type of large language model, right?
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It's not just taking it and it's just like taking its word for it.
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It is having that level of expertise and you know knowledge to be able to consume that data and and review it and send it off.
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That makes sense.
00:20:17.920 --> 00:20:33.680
I mean, if you also imagine if you had a team of of people working on um troubleshooting an issue, you'd have kind of other team members sort of review other uh uh their colleagues' work and kind of go around the circle and make sure everything is is working accordingly and um reviewed accordingly.
00:20:33.759 --> 00:20:36.559
And so I think the same could be probably applied to the AI.
00:20:36.640 --> 00:20:47.440
And um, you know, it's one of those things too where, you know, it's it sounds like it's already being used pretty effectively in the field, but it'll continue to get even better and uh more accurate as time goes on.
00:20:47.519 --> 00:21:00.000
And um things are moving so fast that um yeah, I just can imagine it's just gonna exponentially become more, even more effective and um limit the the kind of inaccuracies if there are any.
00:21:00.559 --> 00:21:06.000
The great part about FastField is you can set the guardrails as high as you want for any type of task, right?
00:21:06.160 --> 00:21:11.759
If you just want the color of the equipment out there, then that is the only the only information that you're gonna get.
00:21:11.839 --> 00:21:18.319
But if you want a full structured readout of of every individual part of that equipment, it's going to do that.
00:21:18.400 --> 00:21:25.039
It's going to fill in, fill in the form that you have pre-populated or put together a structured form based off of the photo.
00:21:25.200 --> 00:21:28.400
But um it's really dependent on how you want to use it, right?
00:21:28.559 --> 00:21:33.039
And the the more you unleash it, the the more information you're going to get back.
00:21:33.119 --> 00:21:34.400
So the more review you'll have.
00:21:34.559 --> 00:21:39.680
But um for basic tasks, it's it's it's pretty pretty accurate.
00:21:40.079 --> 00:21:45.200
So let's, yeah, let's let's talk about how the how FastField fits into an existing stack.
00:21:45.359 --> 00:21:54.079
I know most companies already have uh an ERP, a CRM, some kind of business intelligence uh tool that they're they're attached to and working with.
00:21:54.240 --> 00:21:57.039
Um where does FastField sit in all of that?
00:21:57.200 --> 00:21:59.759
And then how does like plugging into those systems?
00:22:00.160 --> 00:22:02.799
make the data more trustworthy across the the business.
00:22:03.440 --> 00:22:06.559
I think FastField sits on top of the stack that you already have.
00:22:07.039 --> 00:22:09.359
It's the edge that your field team has.
00:22:09.839 --> 00:22:22.240
If you talk about all these different types of systems, whether they're ERP, CRMs, they don't have a a or they might have a field service tool, but it it doesn't have the level of of features that we have.
00:22:22.480 --> 00:22:28.160
It doesn't have the the connective tissue that that we have.
00:22:28.319 --> 00:22:30.640
It's it's simple data collection.
00:22:30.799 --> 00:22:41.839
And if someone's out there trying to do a complex task and then you know dispatch a repair unit based off of this criteria, that's still a manual process within your old system.
00:22:42.000 --> 00:22:49.680
So we like to sit on top of it and then we're going to send um structured and normalized data to those systems to be reported on.
00:22:49.920 --> 00:22:56.559
So that's that's where we sit and it helps thousands and thousands of companies every day.
00:22:56.880 --> 00:23:06.240
Yeah that's that's a I I imagining a a very imagine very welcoming um statement there just in terms of like eliminating that learning curve.
00:23:06.559 --> 00:23:12.880
You don't have to replace your whole the whole stack you have the the the platform you might be using and across your organization.
00:23:12.960 --> 00:23:23.839
Like that that's just going to lower the learning curve associated with with adopting FastField and getting it rolled out across a yeah across your your with your whole team.
00:23:24.480 --> 00:23:26.400
Okay so let's talk about transformation now.
00:23:26.720 --> 00:23:44.480
Plenty of orgs have tried to solve this the the issues that you're solving with with spreadsheets and and um generic sort of like form builders and and sounds like you um you are work you have your own in-house sort of platform producer generator.
00:23:45.680 --> 00:23:49.839
What does the switch to a purpose built field workflow platform actually look like?
00:23:50.480 --> 00:24:05.279
And like what what are you doing to kind of solve some of these uh these these issues what what I always tell individuals when I speak to them for the first time is let's address the biggest issue that you have start there and then and then expand.
00:24:05.440 --> 00:24:29.920
You know I I think the reality is um in this day and age disruption's coming coming and we want to partner with companies to unleash productivity let's get in let's solve that first use case and then kind of go down the line and revitalize the way that you you do your field work on a day-to-day week to week basis that's that's what I like to say is is our pitch for moving off of paper.
00:24:30.240 --> 00:25:33.599
Yeah yeah printing printing costs don't get me started on printing cost it's like the number everyone sort of sort of laughs at until it you know actually added up but um do you have any like uh a real world examples um that you've you haven't already shared um up until this point like maybe a time when when having good field data quickly led to something really really meaningful I don't know a faster decision a cost um that was avoided um I don't know a safety issue that was caught before it turned into a real problem yeah we have a um a great example would be a customer of ours Kellis Vegetation uh they replaced their paper chemical application reports with uh a digitized workflow and they had to hold these paper reports for three years in filing cabinets in their offices and so you can imagine moving from that type of paper process and storage process to you know everything's digitized, everything's in the cloud everything's available to be pulled up within seconds it's it's just a night and day difference of of how they revolutionized the way that they're doing doing business on the day-to-day basis.
00:25:34.160 --> 00:25:45.519
After that very basic you know chemical application report they added vehicle inspections, time clock corrections, you know, equipment calibrizations that that run from math that technicians input into those forms.
00:25:45.680 --> 00:26:13.039
And so um step by step they started you know piecing off other manual processes, other uh paper processes that they had so that they can connect kind of their whole day-to-day their whole workflow together within FastField and anecdotally they are they are better for it um they they seem uh very happy with with what they've implemented in their company and and you know I'm sure that they use offline offline utility as well quite a bit.
00:26:13.359 --> 00:26:27.039
Oh yeah the yeah my my favorite feature personally speaking is the offline capabilities but yeah hearing these examples is um is ultimately I think what's going to resonate with with listeners and viewers um and I'm sure you have a whole slew of examples that you could continue to rattle off.
00:26:27.119 --> 00:26:54.960
Um but I want to um now ask you like kind of uh maybe answer this next question for for the leader the listener who who hasn't like prioritized this sort of um solution yet like there I'm sure there's an operations leader just listening right now who who knows uh that uh is aware of all these problems that we we outlined but the the urgency hasn't hit yet so like what do you say to them and and like what does getting started actually look like with FastField?
00:26:55.279 --> 00:26:59.839
I think to answer that question, your field data problem is quietly expensive.
00:27:00.079 --> 00:27:13.759
Whether it's you know from a headcount perspective or we can't hire enough people to do these tasks, let us partner with you to to automate a lot of these tasks so the individuals that you have are that many more time sufficient, right?
00:27:13.920 --> 00:27:16.960
Let's not run into into the people problem anymore.
00:27:17.119 --> 00:27:31.200
There's you know manual airs there's training there's all of this the way that you can build Fastfield and and the structured guardrails that you can put up it's so much easier to onboard field technicians and and get them up and running.
00:27:31.440 --> 00:27:52.480
And not only that they can start speaking with the back office more quickly and it's just this this seamless way for for different parts of the business to to work with each other versus having a missed call, having a missed inbox um you know if everybody's working within the same ecosystem it's it's just kind of like everybody's rowing in the boat together.
00:27:53.359 --> 00:28:01.200
To directly answer the question I think go back to what I previously said for someone who's listening to this start narrow.
00:28:01.359 --> 00:28:11.839
What is the biggest problem that you have right now you know in the field with with your organization let's solve that take that to your exec sponsor and then expand it to the crew.
00:28:12.000 --> 00:28:27.680
You know this is something that that we can get set up within minutes and then within a matter of 24 hours multiple people within the organization can be can be giving feedback going back and forth on this you know this is the process that we have over here that's manual.
00:28:27.759 --> 00:28:48.160
It's on paper here's a digitized solution that we all can be on the same page together you know you submit something it flags something for me this person's going out you know within the hour versus what do we have right now that that is a real world example of you know how we can change the way somebody acts within their business quite quickly.
00:28:48.480 --> 00:29:16.160
That makes sense very well said yeah it's start start small start with one sort of one form one workflow and and work your way out and and build build up build on top of that I feel like a lot of the listeners um who are um running into that problem of like where to start they're looking at like the the end result like the 12 month sort of version of this and so they they get kind of overwhelmed that they don't you know even start with the two week version right and so you got to start somewhere start small and and see how it works and and go from there.
00:29:16.559 --> 00:29:42.880
I've got one more sort of hard hitting question for you Ross um uh fast fields obviously moving fast you've already mentioned the native sort of form uh building tool in the platform um and I'm sure the AI side of the operations is just constantly unfolding um and that you've got quick base behind you now what's what's on the roadmap and like what should ops leaders be be watching over the next few months?
00:29:43.359 --> 00:30:09.200
I think what we just released in the past couple of months with AI photo insights, asset and team tracking AI workflow, uh label scanner OCR, which allows you to go to uh various you know machinery and equipment or assets that you have in the field and and just tag multiple labels at once to to be able to pull up um oh this is this truck's you know schematics and and exactly what I need to fill out for this form.
00:30:09.599 --> 00:30:27.920
It's a a fantastic feature that cuts down on on time you know to a multiple um task scheduler you know another another great feature that that we released recently but I I think where all of our focus is right now with within this quarter is the new the new ai builder that that is coming out.
00:30:28.079 --> 00:30:35.359
It is is what we believe will allow us to get people up and running within within minutes.
00:30:36.160 --> 00:30:42.559
The proof of concept is within seconds and within minutes you can just start blueprinting out your your company's problem.
00:30:42.799 --> 00:30:53.200
That is that is the focus of of our next two months and and by the time this come out this comes out we will have you know probably gone through v1 two three and it's just going to be that much better.
00:30:53.359 --> 00:31:07.279
But um what we have on the roadmap for Q4, you know stay tuned there's there's a lot there's a lot going on but I don't want to get ahead of myself and I don't want to get in trouble with product and start commit and start committing to to some things that that are still cooking.
00:31:07.519 --> 00:31:18.319
But what we have with with the new builder is is going to truly revolutionize the way that that people can interact with our system and and get set up.
00:31:18.960 --> 00:31:21.440
There's no more barrier to entry from a technical perspective.
00:31:21.599 --> 00:31:24.400
You do not have to have you know a specialist on staff.
00:31:24.480 --> 00:31:39.839
You don't have to train someone for 30, 40 hours on how to build these fields and you know put everything together perfectly it is something that um even the most uninitiated can just jump in and and type out you know a couple of sentences of this is my problem.
00:31:40.079 --> 00:31:41.519
Let's start from there.
00:31:41.839 --> 00:31:44.400
There's a lot to to be excited about that's for sure.
00:31:44.720 --> 00:31:56.960
I I love uh you know the the task scheduler and the photo insights but the the AI builder um seems like there's a ton of uh a ton of potential there and um and I'm excited to see what else you cook up with uh in Q4.
00:31:57.119 --> 00:31:58.559
So maybe we'll have to have you back.
00:31:58.640 --> 00:32:07.759
But um until then where where should people go if they want to dig in and explore more about uh fast field and and what what is you guys have have in the works.
00:32:08.240 --> 00:32:13.599
Come come to our website and start a free trial and and just hop right in.
00:32:13.759 --> 00:32:24.319
It's uh like I said it's the barrier to entry is is pretty low and and we'd love for anybody and everybody to come in and just start playing around with it and and you know give us that feedback.
00:32:24.880 --> 00:33:41.759
You know we have we have a a lot of great um public-facing uh social media blogs you know we have uh two different um events called empower uh through our parent company quickbase that that people can attend every year but um aside from that just getting in there using the tool and and and exploring the art of the possible right um you know every single field service company out there they they have a an unresolved problem that that the bar is too high for them to go and fix let's let's work on it together let's see if we can um you know unravel that ball of yarn that's been there for you know 20 30 years that it's it's always just been kicked down the road right yeah that um totally I I would personally find so much value in that but just getting my hands on and kind of seeing the uh seeing and feeling that's tangible sort of um assets there with the platform um so listeners viewers uh we'll place links down below in the show notes for you to to go and learn more about the platform um go get connected with Ross over on LinkedIn Ross thank you so much for everything you shared with us this has been really insightful episode and um I genuinely would love to have you back and talk updates because I'm sure you have uh there's there's no shortage of things you guys are are cooking up and have in the works.
00:33:41.920 --> 00:33:47.039
So uh we could lead a whole other podcast episode around uh some of the new features and capabilities.
00:33:47.519 --> 00:33:48.319
Thanks for having me.
00:33:48.400 --> 00:33:52.559
It's been a great time all right well thank you all for listening to the SourceForge podcast.
00:33:52.640 --> 00:33:54.160
I am your host Bo Hamilton.
00:33:54.240 --> 00:33:58.960
Make sure to subscribe to stay up to date with all of our upcoming B2B software related podcasts.
00:33:59.119 --> 00:34:00.960
I will talk to you in the next one
00:00:05.200 --> 00:00:08.080
Hello everyone and welcome back to the SourceForge podcast.
00:00:08.160 --> 00:00:14.720
I'm your host, Bo Hamilton, and today we are looking at a problem that affects nearly every business with employees working outside the office.
00:00:14.960 --> 00:00:23.920
So think about a technician who notices a machine starting to fail, or an inspector who finds a safety issue, or maybe a crew that documents damage at a job site.
00:00:24.079 --> 00:00:33.920
All that information can be valuable and time sensitive, of course, but it often gets buried in a form, maybe emailed as a PDF or entered into a spreadsheet that no one reviews until days later.
00:00:34.000 --> 00:00:38.079
And by the time it reaches the person who can act on it, the opportunity may already be gone, right?
00:00:38.159 --> 00:00:39.200
The crew has moved on.
00:00:39.359 --> 00:00:47.280
Maybe another truck has to be sent out or an invoice gets delayed, or maybe even like just a small problem becomes a much more expensive one, right?
00:00:47.359 --> 00:00:50.479
That's that's sort of the issue we're trying to convey here.
00:00:50.560 --> 00:00:58.079
And many companies have already replaced paper forms with apps, but collecting information digitally is only just part of the solution.
00:00:58.240 --> 00:01:03.039
The bigger challenge is turning that information into a decision while it still matters.
00:01:03.200 --> 00:01:06.400
And that is what FastField is designed to do, part of QuickBase.
00:01:06.640 --> 00:01:16.799
FastField helps teams collect information from job sites, think uh plant floors and vehicles and other field environments, and then immediately route it to the right people and the right business systems.
00:01:16.959 --> 00:01:22.959
And its newer AI capabilities can even review job site photos for potential safety, compliance, and equipment issues.
00:01:23.200 --> 00:01:30.560
So joining me to explain how all it works is Ross Marshall, Senior Director of Growth Operations and Finance at FastField.
00:01:30.640 --> 00:01:36.640
Uh, Ross, I'm really excited to get into this discussion and learn more about what it is you're doing over at FastField.
00:01:36.719 --> 00:01:38.560
So um I'm I'm really happy to have you here.
00:01:38.640 --> 00:01:39.920
Welcome to the podcast.
00:01:40.319 --> 00:01:41.439
Thanks for having me, Bo.
00:01:42.000 --> 00:01:49.920
Um now I want to start at the beginning, start with some of the basics here for listeners and viewers who might not be familiar with uh FastField.
00:01:50.000 --> 00:01:53.840
For anyone who hasn't come across FastField before, how would you describe what it does?
00:01:54.239 --> 00:01:55.439
So, what is FastField?
00:01:55.599 --> 00:01:58.400
At its core, FastField is a field data collection software.
00:01:58.560 --> 00:02:06.319
It is for individuals, whether they're out in the field, on a manufacturing floor, um, who need to collect data.
00:02:06.640 --> 00:02:13.199
And going beyond that, it's not simply just the act of turning paper into a digitized form.
00:02:13.280 --> 00:02:15.120
It is, it is what do you do with that data?
00:02:15.360 --> 00:02:21.520
It turns that data into something structured, something that can be routed that is visible to the back office.
00:02:21.680 --> 00:02:26.479
So it's really that connective tissue between the individuals out in the field, the back office.
00:02:26.719 --> 00:02:30.319
It it helps the whole workflow of a field team.
00:02:30.639 --> 00:02:31.840
Okay, the connective tissue.
00:02:31.919 --> 00:02:33.439
I like that um descriptor.
00:02:33.599 --> 00:02:42.400
Um I know I know a lot of teams figure they've already sort of handled a lot of these um these issues with their own sort of patchwork um solutions.
00:02:42.479 --> 00:02:48.080
Um they ditch the clipboards, maybe they've got an app or some sort of basic forums, but where does that usually fall apart?
00:02:48.159 --> 00:02:52.960
And then like what's what's it costing to them that they they don't even see or really take into account?
00:02:53.439 --> 00:02:53.680
Right.
00:02:53.759 --> 00:03:00.800
I I think to answer that question bluntly, it's the individual is not getting that report in a week or with three different spreadsheets.
00:03:00.879 --> 00:03:02.479
They are getting it instantaneously.
00:03:02.639 --> 00:03:05.280
It is a structured system.
00:03:05.680 --> 00:03:10.639
Um, the individual who sets it up, they set up the guardrails, they set up the parameters of of what we want.
00:03:10.800 --> 00:03:14.800
An individual is out there putting together an instant checklist.
00:03:15.120 --> 00:03:29.680
And when that form is filled out and it is submitted, there could be triggers, there could be um alerts that go off, and and the team is working together on that versus just a very plain, basic digital form is you are just digitizing information.
00:03:29.840 --> 00:03:31.840
There's there's nothing behind that.
00:03:32.000 --> 00:03:38.400
And so that's really the difference between our software and just filling out a digitized form.
00:03:38.879 --> 00:03:47.759
Um so I know there's a there's there's a real difference between uh you know a team that's let's say collecting field data and a team that's actually doing something with it.
00:03:47.919 --> 00:03:52.319
Um what does that that gap look like on a day-to-day basis?
00:03:52.479 --> 00:03:56.560
And then like what has to sort of change operationally to close that gap?
00:03:57.039 --> 00:04:01.840
I think it is it is putting together a digital process.
00:04:02.000 --> 00:04:05.199
It's it's not the illusion of a digital process.
00:04:05.280 --> 00:04:07.680
It is the individuals are out doing something.
00:04:07.840 --> 00:04:10.800
What is the downstream impact of that data, right?
00:04:11.120 --> 00:04:16.480
Is it we are looking, we are looking for, you know, audits of of trucks.
00:04:16.639 --> 00:04:34.319
And, you know, if there's a certain amount that that don't pass this, it flags for, you know, repair technician to to go out there versus having a bunch of information kind of siloed in an inbox or into a Excel spreadsheet that ultimately someone needs to ten key in that information and then review that information.
00:04:34.480 --> 00:04:38.319
It is the ability for those teams to work harmoniously together.
00:04:38.480 --> 00:04:47.120
And then the next step after that is to to get those work orders out, to get those, you know, those other job orders starting sooner than later.
00:04:47.439 --> 00:04:47.680
Yeah.
00:04:47.759 --> 00:04:58.319
So it sounds like it's it's the a lot of the bottleneck is really just it filters down to you know, a person just forgetting um to check on certain information or follow up.
00:04:58.480 --> 00:05:03.600
Um it's just uh it whittles down to a person remembering to check on the thing they're supposed to check on.
00:05:03.759 --> 00:05:16.160
Um and if you're building something that uh, you know, like a safety program, the issues there can really um start to unfold in uh unintended ways and the ways that you don't want to happen.
00:05:16.319 --> 00:05:20.879
Um walk me through what happens like the second someone hits submit on a form.
00:05:21.120 --> 00:05:23.439
Like where does that where does that data go?
00:05:23.600 --> 00:05:24.879
Uh, who sees it?
00:05:25.040 --> 00:05:28.079
How does it get to the right person to act on it?
00:05:28.480 --> 00:05:36.720
Depending on the rules that that you set up, once you hit submit, it can go to an inbox, it can go to the cloud, straight to an ERP, CCMS, SQL Server.
00:05:36.959 --> 00:05:43.920
Um one field event becomes a back office record, a notification, a trigger task to be done.
00:05:44.079 --> 00:05:54.879
And so it really depends on on how you set that up, but um, these forms are embedded in your tablet, phone, what whatever else you're bringing out into the field.
00:05:55.040 --> 00:05:57.839
And so there's there's a whole workflow behind it.
00:05:58.000 --> 00:06:01.920
Um the beautiful thing about Fast Field is it it works offline.
00:06:02.079 --> 00:06:10.000
So if you are out on an oil rig or you're you know four or five stories below ground in a basement, you can still do your work.
00:06:10.160 --> 00:06:18.000
You can still have all of the information that you need in front of you, be able to query it and um complete your tasks and submit.
00:06:18.399 --> 00:06:23.839
Once you get connectivity again, then those reports go you know through their normal workflows.
00:06:24.000 --> 00:06:31.839
So just because you are out of connectivity doesn't mean that you you have to go back to paper or that things aren't working.
00:06:32.000 --> 00:06:36.480
So it's a it's a it's a fantastic feature that we've had for for quite some time now.
00:06:36.800 --> 00:06:37.360
Yeah, okay.
00:06:37.439 --> 00:06:48.879
I was gonna ask about like what happens, you know, when you're you're working out in the middle of nowhere, there's no signal, no service, you know, the the um Starlink isn't connecting, or you're underground, um, you have that offline access.
00:06:49.040 --> 00:06:52.079
How long has that been a feature, been a part of the system?
00:06:52.639 --> 00:06:53.759
It it has been around.
00:06:53.839 --> 00:07:07.439
I I joined in 2019 and it was it was around then, so we've had it for quite some time, and it's it's really the differentiator between individuals looking at, okay, I need to move from paper to digitizing a form, but what's really behind that?
00:07:07.600 --> 00:07:17.279
Can you go out in the field and and continue to do your your day-to-day with with just you know a basic fields and and lists name, right?
00:07:17.439 --> 00:07:19.279
There's there's certainly more behind that.
00:07:19.439 --> 00:07:23.600
And once you get back to connectivity, you know, what's what's really the process there?
00:07:23.759 --> 00:07:24.959
Does it does it sync?
00:07:25.040 --> 00:07:27.279
You know, can can you receive new information?
00:07:27.439 --> 00:07:36.639
So that's where FastFuel, it's all interconnected and and and it helps people, you know, whether they're online or offline, can continue to do their day job.
00:07:36.959 --> 00:07:50.639
Yeah, it seems like it seems like one of those features that um it's almost like a boring feature, but it has like a really real-world like tangible use case, um, especially when you talk about those oil refinery rigs or you know, some underground operations.
00:07:50.800 --> 00:08:05.839
Um, and then it's also one of those features that's increasingly harder to come by, having offline support in today's world where you're constantly, you know, sending data up to the cloud and and uh using AI to run on multiple like uh cloud-based remote servers.
00:08:06.000 --> 00:08:14.079
Um you don't really see offline support um as much nowadays with with our sort of various services we all use and love and whatnot.
00:08:14.240 --> 00:08:16.480
So um that is pretty exciting.
00:08:16.560 --> 00:08:26.000
And uh it's again, like you're you're uh the offline piece, it doesn't sound particularly exciting until you're you're in a basement or like a substation or something like that.
00:08:26.399 --> 00:08:26.720
Right.
00:08:26.800 --> 00:08:30.720
It it's it's certainly an exciting feature for individuals who are out in the field.
00:08:30.879 --> 00:08:45.759
You know, for for you and I, possibly sitting in an office all day, it is um it it it seems like table stakes, but to be out, you know, on an oil rig or you know, servicing, you know, a substation, it it is, it's it's a game changer.
00:08:45.840 --> 00:08:49.360
It it changes the way that people can can do their day-to-day.
00:08:49.600 --> 00:08:54.159
And um, you know, I have a a great anecdotal example.
00:08:54.320 --> 00:09:00.080
I was at a uh a pizza parlor about a week ago with my son for his baseball team, and three individuals walked up.
00:09:00.159 --> 00:09:01.120
They had a black polo.
00:09:01.200 --> 00:09:09.919
I I won't share the logo, but they tapped me on the shoulder and I was a bit startled, and and the guy, you know, extended his hand and I shook it, and he's like, You work at Fastfield?
00:09:10.000 --> 00:09:12.720
And I go, I do work at Fastfield, I've been there for about six years.
00:09:12.879 --> 00:09:19.279
He goes, You guys have changed, has fundamentally changed the way that we work on a day-to-day basis.
00:09:19.519 --> 00:09:28.720
We're we're out in the field servicing fences and and electrical, you know, boxes, and you fundamentally have changed the way that we do things.
00:09:28.879 --> 00:09:31.919
And you have saved us each 20, 30 hours a week.
00:09:32.000 --> 00:09:33.120
And there was there's three of them.
00:09:33.200 --> 00:09:37.120
It's just like, you know, those types of stories, they they make you feel good.
00:09:37.279 --> 00:09:52.720
And I kind of like, you know, walked away from that and was just like, that that was a fantastic out-of-the-blue scenario, but um just an example of how how offline capabilities, you know, help help people shave 20, 30 hours off their work week.
00:09:53.039 --> 00:09:58.480
So you've I wanted to get into the AI aspect, because of course you have AI workflows built into the platform.
00:09:58.720 --> 00:10:00.879
What does that look like in the real world?
00:10:01.039 --> 00:10:03.279
Like how's it sort of how's it flagging problems?
00:10:03.440 --> 00:10:11.279
How's it routing things to the right people, servicing stuff that would otherwise just sort of like, you know, be buried in a spreadsheet or someone's inbox?
00:10:11.679 --> 00:10:11.919
Right.
00:10:12.000 --> 00:10:18.639
It it's really the difference between an inbox someone has to triage and a system that triages itself.
00:10:18.879 --> 00:10:33.120
It's it's making real-time decisions based off of guardrails that an individual sets up, but it's it's really, you know, flagging anomalies, prioritizing urgent items, you know, catching missing data within forms.
00:10:33.200 --> 00:10:42.879
And so it is, it's it's like that ride-along co-pilot for for you as a manager or an operator to to make sure that everybody out in the field you know is kind of within these boxes.
00:10:43.039 --> 00:10:53.600
You can imagine in highly regulated environments, it's it's not important, it's imperative to have something like this, to make sure things aren't missed, that thing, things are absolutely structured the way that they should be.
00:10:53.759 --> 00:11:06.799
So it's it's a fantastic feature that that helps reduce various types of um you know data inconsistencies or having to go back and rework it, or or well, these four fields aren't filled out towards the bottom.
00:11:06.879 --> 00:11:07.440
What happened here?
00:11:07.519 --> 00:11:15.440
Well, I need to go back to the job site and and reinspect because you know I forgot it at that point versus having a feature that flags it while you're there.
00:11:15.519 --> 00:11:18.399
You can't submit until until this is done.
00:11:18.639 --> 00:11:23.600
So it cuts down on time, cuts down on cost, um, it helps everybody.
00:11:23.919 --> 00:11:37.039
Yeah, I don't think it could be overstated just how you know helpful, like just relatively simple things like like really effective reminders um and and um like uh summarization of like dense information.
00:11:37.200 --> 00:11:46.320
And then if you're able to have some of these AIs and maybe agentic capabilities act like take on small repetitive tasks on a user's behalf.
00:11:46.480 --> 00:11:57.360
Um, yeah, I I'd be curious to like could learn more and hear more about like the um some of the specific features that the um you have built in in regards to what AI is doing here.
00:11:57.600 --> 00:12:00.639
Have you guys uh incorporated a lot of like agentic features?
00:12:01.120 --> 00:12:18.399
We we have, I think um some of the the biggest ones that I could point out would be our AI photo insights, where you can, you know, walk around a work site with your phone and and just capture uh a truck and it will it'll look at the image, it'll read it, and it'll start describing it to you.
00:12:18.559 --> 00:12:24.159
You know, the the front left tire has has wear and tear on the you know top left section of it.
00:12:24.240 --> 00:12:29.360
Or you're um a great real real world example I dealt with last week was uh an HVAC servicer.
00:12:29.440 --> 00:12:33.759
They're going around and you know, taking the tablet and looking at an HVAC unit.
00:12:33.919 --> 00:12:40.799
Um, top left-hand corner, there's corroded wires, which you know is is leading to possible, you know, burn scarring right there.
00:12:40.960 --> 00:12:47.120
Um the the housing unit of the HVAC, you know, there's screws that are loose, so it's it's open to the elements, things like that.
00:12:47.200 --> 00:13:03.200
It is describing it, it's rating it, and then it's providing essentially an incident report so that if you don't have something structured, it can it can create that for you, and it's it's cutting down on an inspection to two minutes rather than an hour, right?
00:13:03.440 --> 00:13:10.240
So it's a a fantastic feature that we recently launched, um, not three months ago.
00:13:10.480 --> 00:13:13.440
And it it has amazing real-world applications.
00:13:13.519 --> 00:13:16.720
Um, another great example would be just going through manufacturing floors.
00:13:16.960 --> 00:13:25.679
You can imagine, especially with uh a gigantic piece of machinery, the the amount of detail that can possibly be on that.
00:13:25.840 --> 00:13:39.679
Um, but taking a tablet or a phone and and just slowly just capturing it as as a video and and the AI analyzing the entire piece and and producing you know an incident report or an inspection report on something like that.
00:13:39.759 --> 00:13:44.960
It's it cuts down to minutes, what what could take an hour plus.
00:13:45.600 --> 00:14:06.159
So the the future is now truly with with how fast things are moving, you know, where we were five years ago, uh being just kind of basic data collection with with these few add-on features, and now we're starting to progress into um having these types of co-pilots ride with you in in your day-to-day to cut down your processes, you know, two minutes.
00:14:06.399 --> 00:14:09.519
Um obviously there's always the human element behind it, right?
00:14:09.840 --> 00:14:14.159
AI is not going to be the person that goes out there and and does everything.
00:14:14.320 --> 00:14:24.159
There are experts that are gonna go out there, use these tools to collect data rapidly, and then be able to use their experience, their judgment calls to say, you know, look, all of this looks great.
00:14:24.240 --> 00:14:26.720
This piece over here, I'm gonna annotate a little bit differently.
00:14:26.799 --> 00:14:33.840
You know, I see something over here that might not be right, so I'm gonna go and, you know, take a picture myself and submit it and write my own notes.
00:14:34.000 --> 00:14:40.480
But it it's it's that that co-pilot that really just kind of gives you a superpower out in the field.
00:14:40.720 --> 00:14:55.440
Um moving on to the next piece that that we we want to talk about is what we are releasing in August for for everybody is a true vibe coding platform for building a form.
00:14:55.679 --> 00:15:04.080
Um sometimes a barrier to entry for for anybody moving off paper is learning a new system, being able to go in and learn that tool.
00:15:04.240 --> 00:15:07.120
You know, do I have to have an expert who knows this tool?
00:15:07.360 --> 00:15:15.440
I always believe that Fast Field, the technology bar was quite low for us to be able to get in there, get your hands dirty, and build out a form.
00:15:15.759 --> 00:15:29.039
I believe, you know, what we're releasing in August, you just go in there and you do a very simple language prompt of what you want as a form and and what you need it to solve, and it will produce it for you within seconds.
00:15:29.279 --> 00:15:34.399
Within a matter of minutes, you are starting to build out an entire workflow for your operation.
00:15:34.559 --> 00:15:45.519
So I believe we've moved the bar down to our shoelaces, and anybody and everybody can start a trial with Fastfield and and be up and running within minutes.
00:15:45.759 --> 00:15:53.279
Um, it's a great time to be alive, and it is amazing to see the power of these kind of agentic systems.
00:15:53.600 --> 00:15:58.399
Not to not to date this podcast, but so it's probably already out uh for listeners and viewers.
00:15:58.559 --> 00:16:08.159
Um that is I I want to ask you, uh I want to get more into um unraveling, kind of some unpacking some of the features here with this platform and the AI specific features.
00:16:08.320 --> 00:16:13.519
You mentioned one thing that that caught my ear was um you mentioned the incident reporting in some of the examples.
00:16:13.679 --> 00:16:28.320
And I I want to talk about some of the high-stakes use cases like uh surrounding like safety and compliance, um, where a data gap can really sort of be a big a big issue that really bites and causes some real problems if if um things go missing.
00:16:28.559 --> 00:16:35.600
Um how do you how do you help teams get out of a reactive sort of incident reporting and into something a bit more proactive?
00:16:35.759 --> 00:16:41.200
And then like what does that shift sort of look like on the ground in the in the real world?
00:16:41.679 --> 00:16:43.039
You took the words right out of my mouth.
00:16:43.279 --> 00:16:47.279
What we always say is, you know, reactive incident reporting becomes a proactive system.
00:16:47.519 --> 00:16:56.240
And it is it's allowing companies to have a validation system that that happens at time of capture, not after, right?
00:16:56.480 --> 00:17:12.799
It's it is immediately while someone is there, while while the action is happening versus inputting in data and then five business days later that we we realize that you know we have um a machine who has tripped this many times and it's above our KPI threshold.
00:17:12.880 --> 00:17:25.119
And so it's it it breaks down on the time of you know safety and compliance and and how we support people, you know, be more buttoned up with their safety and compliance.
00:17:25.599 --> 00:17:25.839
Okay.
00:17:25.920 --> 00:17:39.279
And then you mentioned obviously the the photo insights uh part of the platform, AI looking at photos from the field in real time and and catching all sorts of like compliance issues uh before a person even sort of sort of like opens them up.
00:17:39.440 --> 00:17:43.119
Um I want to I want to like have you unravel that some more.
00:17:43.279 --> 00:17:44.319
Like how does that work?
00:17:44.480 --> 00:17:51.759
Um you mentioned you just hold up the tablet and just kind of scan the problem area, the area you want to find out, you know, learn learn more information about.
00:17:51.920 --> 00:17:58.880
Um and then yeah, what is it, what does it just change about inspections and quality workflows when AI is kind of taking that first pass?
00:17:59.599 --> 00:18:12.720
Instead of data dumping into a folder, you know, 150 uncategorized photos, it is returning structured findings based off of a photo, uh, a selection of photos, a video.
00:18:12.880 --> 00:18:17.440
It's identifying defects, hazards, very basic observations.
00:18:17.599 --> 00:18:25.440
And so it's it's putting together just a structured format versus having, again, you know, 150 uncategorized photos.
00:18:25.519 --> 00:18:29.599
It's it's giving you a severity rating, a confidence score.
00:18:29.680 --> 00:18:36.480
It's it's allowing you to really up-level your safety and compliance, incident reporting, you you name it.
00:18:36.559 --> 00:18:43.759
It's it's it's cutting down on all these individual steps that that companies deal with on a day-to-day basis.
00:18:44.400 --> 00:18:49.359
Do you uh how do you deal with the the false positives aspect?
00:18:49.519 --> 00:18:53.119
Um, because I imagine like, you know, AI is not is not perfect.
00:18:53.279 --> 00:18:59.200
Um, there's always going to be a little bit of like uh some issues, and that's that's why you kind of need a human in the loop to review things.
00:18:59.359 --> 00:19:07.519
Um but uh how do you, yeah, how have you sort of factored in that um sort of potential there with with false positives and some images?
00:19:08.079 --> 00:19:09.839
Human judgment always stays in the loop.
00:19:09.920 --> 00:19:10.400
You said it.
00:19:10.480 --> 00:19:23.920
It it is before I submit this form, just because this photo is filling out this form, it's giving me loads worth of data, it's going through and and and validating that that it is all correct.
00:19:24.079 --> 00:19:32.160
Um a a digital form that could have taken you 30, 40 minutes to fill out now takes you, you know, two, three minutes to fill out.
00:19:32.319 --> 00:19:48.319
But there's still that level of of human judgment um to go through there, make sure that that that everything is not only correct, but that it is you know structured in the way that it's not going to fire off an incident report because you know it's it's making it's making a wrong assumption, right?
00:19:48.400 --> 00:19:55.519
We're trying to um say that that this part of the equipment is is faulty when it's tying it back to a different part.
00:19:55.680 --> 00:20:03.279
And so there's always that human element um before submitting, you know, no different than using any type of large language model, right?
00:20:03.440 --> 00:20:06.960
It's not just taking it and it's just like taking its word for it.
00:20:07.039 --> 00:20:16.799
It is having that level of expertise and you know knowledge to be able to consume that data and and review it and send it off.
00:20:17.200 --> 00:20:17.839
That makes sense.
00:20:17.920 --> 00:20:33.680
I mean, if you also imagine if you had a team of of people working on um troubleshooting an issue, you'd have kind of other team members sort of review other uh uh their colleagues' work and kind of go around the circle and make sure everything is is working accordingly and um reviewed accordingly.
00:20:33.759 --> 00:20:36.559
And so I think the same could be probably applied to the AI.
00:20:36.640 --> 00:20:47.440
And um, you know, it's one of those things too where, you know, it's it sounds like it's already being used pretty effectively in the field, but it'll continue to get even better and uh more accurate as time goes on.
00:20:47.519 --> 00:21:00.000
And um things are moving so fast that um yeah, I just can imagine it's just gonna exponentially become more, even more effective and um limit the the kind of inaccuracies if there are any.
00:21:00.559 --> 00:21:06.000
The great part about FastField is you can set the guardrails as high as you want for any type of task, right?
00:21:06.160 --> 00:21:11.759
If you just want the color of the equipment out there, then that is the only the only information that you're gonna get.
00:21:11.839 --> 00:21:18.319
But if you want a full structured readout of of every individual part of that equipment, it's going to do that.
00:21:18.400 --> 00:21:25.039
It's going to fill in, fill in the form that you have pre-populated or put together a structured form based off of the photo.
00:21:25.200 --> 00:21:28.400
But um it's really dependent on how you want to use it, right?
00:21:28.559 --> 00:21:33.039
And the the more you unleash it, the the more information you're going to get back.
00:21:33.119 --> 00:21:34.400
So the more review you'll have.
00:21:34.559 --> 00:21:39.680
But um for basic tasks, it's it's it's pretty pretty accurate.
00:21:40.079 --> 00:21:45.200
So let's, yeah, let's let's talk about how the how FastField fits into an existing stack.
00:21:45.359 --> 00:21:54.079
I know most companies already have uh an ERP, a CRM, some kind of business intelligence uh tool that they're they're attached to and working with.
00:21:54.240 --> 00:21:57.039
Um where does FastField sit in all of that?
00:21:57.200 --> 00:21:59.759
And then how does like plugging into those systems?
00:22:00.160 --> 00:22:02.799
make the data more trustworthy across the the business.
00:22:03.440 --> 00:22:06.559
I think FastField sits on top of the stack that you already have.
00:22:07.039 --> 00:22:09.359
It's the edge that your field team has.
00:22:09.839 --> 00:22:22.240
If you talk about all these different types of systems, whether they're ERP, CRMs, they don't have a a or they might have a field service tool, but it it doesn't have the level of of features that we have.
00:22:22.480 --> 00:22:28.160
It doesn't have the the connective tissue that that we have.
00:22:28.319 --> 00:22:30.640
It's it's simple data collection.
00:22:30.799 --> 00:22:41.839
And if someone's out there trying to do a complex task and then you know dispatch a repair unit based off of this criteria, that's still a manual process within your old system.
00:22:42.000 --> 00:22:49.680
So we like to sit on top of it and then we're going to send um structured and normalized data to those systems to be reported on.
00:22:49.920 --> 00:22:56.559
So that's that's where we sit and it helps thousands and thousands of companies every day.
00:22:56.880 --> 00:23:06.240
Yeah that's that's a I I imagining a a very imagine very welcoming um statement there just in terms of like eliminating that learning curve.
00:23:06.559 --> 00:23:12.880
You don't have to replace your whole the whole stack you have the the the platform you might be using and across your organization.
00:23:12.960 --> 00:23:23.839
Like that that's just going to lower the learning curve associated with with adopting FastField and getting it rolled out across a yeah across your your with your whole team.
00:23:24.480 --> 00:23:26.400
Okay so let's talk about transformation now.
00:23:26.720 --> 00:23:44.480
Plenty of orgs have tried to solve this the the issues that you're solving with with spreadsheets and and um generic sort of like form builders and and sounds like you um you are work you have your own in-house sort of platform producer generator.
00:23:45.680 --> 00:23:49.839
What does the switch to a purpose built field workflow platform actually look like?
00:23:50.480 --> 00:24:05.279
And like what what are you doing to kind of solve some of these uh these these issues what what I always tell individuals when I speak to them for the first time is let's address the biggest issue that you have start there and then and then expand.
00:24:05.440 --> 00:24:29.920
You know I I think the reality is um in this day and age disruption's coming coming and we want to partner with companies to unleash productivity let's get in let's solve that first use case and then kind of go down the line and revitalize the way that you you do your field work on a day-to-day week to week basis that's that's what I like to say is is our pitch for moving off of paper.
00:24:30.240 --> 00:25:33.599
Yeah yeah printing printing costs don't get me started on printing cost it's like the number everyone sort of sort of laughs at until it you know actually added up but um do you have any like uh a real world examples um that you've you haven't already shared um up until this point like maybe a time when when having good field data quickly led to something really really meaningful I don't know a faster decision a cost um that was avoided um I don't know a safety issue that was caught before it turned into a real problem yeah we have a um a great example would be a customer of ours Kellis Vegetation uh they replaced their paper chemical application reports with uh a digitized workflow and they had to hold these paper reports for three years in filing cabinets in their offices and so you can imagine moving from that type of paper process and storage process to you know everything's digitized, everything's in the cloud everything's available to be pulled up within seconds it's it's just a night and day difference of of how they revolutionized the way that they're doing doing business on the day-to-day basis.
00:25:34.160 --> 00:25:45.519
After that very basic you know chemical application report they added vehicle inspections, time clock corrections, you know, equipment calibrizations that that run from math that technicians input into those forms.
00:25:45.680 --> 00:26:13.039
And so um step by step they started you know piecing off other manual processes, other uh paper processes that they had so that they can connect kind of their whole day-to-day their whole workflow together within FastField and anecdotally they are they are better for it um they they seem uh very happy with with what they've implemented in their company and and you know I'm sure that they use offline offline utility as well quite a bit.
00:26:13.359 --> 00:26:27.039
Oh yeah the yeah my my favorite feature personally speaking is the offline capabilities but yeah hearing these examples is um is ultimately I think what's going to resonate with with listeners and viewers um and I'm sure you have a whole slew of examples that you could continue to rattle off.
00:26:27.119 --> 00:26:54.960
Um but I want to um now ask you like kind of uh maybe answer this next question for for the leader the listener who who hasn't like prioritized this sort of um solution yet like there I'm sure there's an operations leader just listening right now who who knows uh that uh is aware of all these problems that we we outlined but the the urgency hasn't hit yet so like what do you say to them and and like what does getting started actually look like with FastField?
00:26:55.279 --> 00:26:59.839
I think to answer that question, your field data problem is quietly expensive.
00:27:00.079 --> 00:27:13.759
Whether it's you know from a headcount perspective or we can't hire enough people to do these tasks, let us partner with you to to automate a lot of these tasks so the individuals that you have are that many more time sufficient, right?
00:27:13.920 --> 00:27:16.960
Let's not run into into the people problem anymore.
00:27:17.119 --> 00:27:31.200
There's you know manual airs there's training there's all of this the way that you can build Fastfield and and the structured guardrails that you can put up it's so much easier to onboard field technicians and and get them up and running.
00:27:31.440 --> 00:27:52.480
And not only that they can start speaking with the back office more quickly and it's just this this seamless way for for different parts of the business to to work with each other versus having a missed call, having a missed inbox um you know if everybody's working within the same ecosystem it's it's just kind of like everybody's rowing in the boat together.
00:27:53.359 --> 00:28:01.200
To directly answer the question I think go back to what I previously said for someone who's listening to this start narrow.
00:28:01.359 --> 00:28:11.839
What is the biggest problem that you have right now you know in the field with with your organization let's solve that take that to your exec sponsor and then expand it to the crew.
00:28:12.000 --> 00:28:27.680
You know this is something that that we can get set up within minutes and then within a matter of 24 hours multiple people within the organization can be can be giving feedback going back and forth on this you know this is the process that we have over here that's manual.
00:28:27.759 --> 00:28:48.160
It's on paper here's a digitized solution that we all can be on the same page together you know you submit something it flags something for me this person's going out you know within the hour versus what do we have right now that that is a real world example of you know how we can change the way somebody acts within their business quite quickly.
00:28:48.480 --> 00:29:16.160
That makes sense very well said yeah it's start start small start with one sort of one form one workflow and and work your way out and and build build up build on top of that I feel like a lot of the listeners um who are um running into that problem of like where to start they're looking at like the the end result like the 12 month sort of version of this and so they they get kind of overwhelmed that they don't you know even start with the two week version right and so you got to start somewhere start small and and see how it works and and go from there.
00:29:16.559 --> 00:29:42.880
I've got one more sort of hard hitting question for you Ross um uh fast fields obviously moving fast you've already mentioned the native sort of form uh building tool in the platform um and I'm sure the AI side of the operations is just constantly unfolding um and that you've got quick base behind you now what's what's on the roadmap and like what should ops leaders be be watching over the next few months?
00:29:43.359 --> 00:30:09.200
I think what we just released in the past couple of months with AI photo insights, asset and team tracking AI workflow, uh label scanner OCR, which allows you to go to uh various you know machinery and equipment or assets that you have in the field and and just tag multiple labels at once to to be able to pull up um oh this is this truck's you know schematics and and exactly what I need to fill out for this form.
00:30:09.599 --> 00:30:27.920
It's a a fantastic feature that cuts down on on time you know to a multiple um task scheduler you know another another great feature that that we released recently but I I think where all of our focus is right now with within this quarter is the new the new ai builder that that is coming out.
00:30:28.079 --> 00:30:35.359
It is is what we believe will allow us to get people up and running within within minutes.
00:30:36.160 --> 00:30:42.559
The proof of concept is within seconds and within minutes you can just start blueprinting out your your company's problem.
00:30:42.799 --> 00:30:53.200
That is that is the focus of of our next two months and and by the time this come out this comes out we will have you know probably gone through v1 two three and it's just going to be that much better.
00:30:53.359 --> 00:31:07.279
But um what we have on the roadmap for Q4, you know stay tuned there's there's a lot there's a lot going on but I don't want to get ahead of myself and I don't want to get in trouble with product and start commit and start committing to to some things that that are still cooking.
00:31:07.519 --> 00:31:18.319
But what we have with with the new builder is is going to truly revolutionize the way that that people can interact with our system and and get set up.
00:31:18.960 --> 00:31:21.440
There's no more barrier to entry from a technical perspective.
00:31:21.599 --> 00:31:24.400
You do not have to have you know a specialist on staff.
00:31:24.480 --> 00:31:39.839
You don't have to train someone for 30, 40 hours on how to build these fields and you know put everything together perfectly it is something that um even the most uninitiated can just jump in and and type out you know a couple of sentences of this is my problem.
00:31:40.079 --> 00:31:41.519
Let's start from there.
00:31:41.839 --> 00:31:44.400
There's a lot to to be excited about that's for sure.
00:31:44.720 --> 00:31:56.960
I I love uh you know the the task scheduler and the photo insights but the the AI builder um seems like there's a ton of uh a ton of potential there and um and I'm excited to see what else you cook up with uh in Q4.
00:31:57.119 --> 00:31:58.559
So maybe we'll have to have you back.
00:31:58.640 --> 00:32:07.759
But um until then where where should people go if they want to dig in and explore more about uh fast field and and what what is you guys have have in the works.
00:32:08.240 --> 00:32:13.599
Come come to our website and start a free trial and and just hop right in.
00:32:13.759 --> 00:32:24.319
It's uh like I said it's the barrier to entry is is pretty low and and we'd love for anybody and everybody to come in and just start playing around with it and and you know give us that feedback.
00:32:24.880 --> 00:33:41.759
You know we have we have a a lot of great um public-facing uh social media blogs you know we have uh two different um events called empower uh through our parent company quickbase that that people can attend every year but um aside from that just getting in there using the tool and and and exploring the art of the possible right um you know every single field service company out there they they have a an unresolved problem that that the bar is too high for them to go and fix let's let's work on it together let's see if we can um you know unravel that ball of yarn that's been there for you know 20 30 years that it's it's always just been kicked down the road right yeah that um totally I I would personally find so much value in that but just getting my hands on and kind of seeing the uh seeing and feeling that's tangible sort of um assets there with the platform um so listeners viewers uh we'll place links down below in the show notes for you to to go and learn more about the platform um go get connected with Ross over on LinkedIn Ross thank you so much for everything you shared with us this has been really insightful episode and um I genuinely would love to have you back and talk updates because I'm sure you have uh there's there's no shortage of things you guys are are cooking up and have in the works.
00:33:41.920 --> 00:33:47.039
So uh we could lead a whole other podcast episode around uh some of the new features and capabilities.
00:33:47.519 --> 00:33:48.319
Thanks for having me.
00:33:48.400 --> 00:33:52.559
It's been a great time all right well thank you all for listening to the SourceForge podcast.
00:33:52.640 --> 00:33:54.160
I am your host Bo Hamilton.
00:33:54.240 --> 00:33:58.960
Make sure to subscribe to stay up to date with all of our upcoming B2B software related podcasts.
00:33:59.119 --> 00:34:00.960
I will talk to you in the next one
