SELLEST OSAST
Video feels like the “obvious” way to teach software until you’re the one stuck updating walkthroughs after every release. We sit down with Sagar Garuda, founder and CEO of Zenious, to talk about the real bottleneck behind product education videos: the editing, the reviews, the sync work, and the high cost of keeping content current when a SaaS product changes fast.
We follow Sagar’s path from engineering to technical writing, then through customer education leadership at fast-growing startups, where onboarding speed and tribal knowledge become existential scaling problems. He explains how multiple teams describe the same product differently across the customer journey and why technical writers create the most value when they stop operating in silos and start orchestrating a single source of truth across help portals, knowledge bases, LMS content, and digital adoption platforms.
Then we get concrete about how Zenious approaches the workflow: record your screen, speak naturally, and let transcript-based editing handle polishing, tightening, and syncing audio to what’s happening on screen. We also explore why structured documentation matters more in the AI era, how “knowledge layers” power contextual AI, and where human judgment still beats automation when deciding what belongs in customer-facing content.
If you’re building a documentation strategy, scaling customer education, or trying to make video sustainable for your team, subscribe, share this with a content friend, and leave a review with your biggest challenge: what’s the one thing that keeps you from shipping more video?
Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.
Show Credits
- Intro and outro music - Az
- Audio engineer - RJ Basilio
Interested in being on the show? Let's connect.
NÄITA MÄRKUSI 🔗
TRANSKRIBEERI 🔗
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Hello friends and welcome to season eight of Inside Tech Comm with Zohra Mutabanna.
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This season features a collection of conversations that explore the ideas, challenges, and opportunities shaping technical communication today.
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From AI and content strategy to leadership, product thinking, and the future of our profession.
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Each episode offers a fresh perspective from people doing the work.
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Let's get started.
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Season eight is proudly sponsored by LavaCon.
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Use discount code ITC26 to save $200 on registration for this year's conference.
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I'll share more about LavaCon later in this episode.
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Today we have on our show Sagar Garuda from India.
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And he was introduced to me by Nibu Thomas.
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And I'm so grateful that we got to interact.
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And here we are.
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Sagar, welcome to our show.
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And please introduce yourself.
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Thank you for so much for having me, Zohra.
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It's my pleasure to be on this show.
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Being a technical writer, like you know, growing up, I never knew that there was a field called technical writing.
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I'm an engineer by qualification and uh I did electronics engineering.
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And never in my wildest dreams, I thought I would become a technical writer.
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While I was in college, I used to write quite a lot.
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I used to write for the college editorial.
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Writing came very naturally to me.
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So after I joined mainstream and when I was in uh when I donned multiple hats while I was still figuring out what would be the right career path for me and working in multiple roles in multiple companies, you know, I could I'll dig into the story of how I eventually became a technical writer.
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But when the field opened and when a person approached me and said, Would you want to become a technical writer?
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We have a position open, and that came out of the blue.
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I didn't realize that companies would pay you to do what you love, which is writing.
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So yeah.
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Technical writing happened to me.
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I didn't plan for it, but right now I'm the founder uh CEO of Zenious.
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But this is something that I've been mulling for a long time.
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I won't say this the transition happened naturally, but being an entrepreneur is a very different ballgame.
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So it comes with you give up on a comfort of a paycheck, you give up on a comfort of stability, and then you're looking at a long time of uncertainty.
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So I had to think hard to kind of make sure that this wasn't a midlife crisis, and if this was something that I really wanted to do, and I needed to convince, not rather convince, I needed to get the biggest stakeholder in my life on board, you know, which is my wife, and she was all for it, uh, to my surprise.
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And uh, you know, the journey started then.
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So it's been a journey over decades, which started off in sales and then transitioned to support, then uh did QA for some time, then a technical writer, then an instructional designer, then in customer education, across companies like Oracle and Computer Associates, which were these huge corporates with you know very large writing teams, where I honed my skills around the basics of technical writing and instructional designing, and saw how a steady state looks like in an organization.
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And then for another decade, I took my learnings to a next level in three startups, uh two of which eventually turned unicorns, Zenoti and Darwinbox, where I was the head of customer education and I launched two academies, Darwinbox Academy and Zenoti University.
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I would have certified uh over 25,000 people, they would have certificates with my signature on it.
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So very humbled and you know blessed to have had that experience.
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Yeah, so that's been my journey so far.
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Now I've been away from India for a long time, and the traditional path to stability has been engineering.
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So when you discovered technical writing, did technical writing pay on par with engineering, or did you have to convince yourself that this is what I wanted to do or family?
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Technical writing, believe it or not, pays more than a developer and little less than a product manager, in my experience.
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I can safely say that technical writing has funded my entrepreneurial journey.
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It did pay off by working in startups which eventually turned unicorns and the stock.
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I worked with very generous founders, the founders who needed problems to be solved.
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And the founders that I work with saw instructional designing and technical writing as a key area that needed to be done right for the company to grow to the next level.
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So my sweet spot was getting into companies that had started to gain traction, and then they would be getting in so many customers, and then unless you are able to onboard them faster, there is no way that you're able to scale, number one.
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And then when the growth hits you, you also start to add so many employees.
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You know, your champions do not have time to train the best of the people.
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So there is all this tribal knowledge which is in their heads, and that needs to be put out in a structured manner.
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Now, while it's easy to say, how about you just somebody record something and then give it to everyone, and then they just like you know, they take it and run from there.
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Companies take some time to understand that it's not that easy.
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There is a science to it, there is a structure to it.
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There are some principles that you need to follow where people are able to understand the holistic picture.
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Next, understand the nuances.
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So many things need to come together.
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So, for that, you need a competent customer education team which is able to see every aspect of your company.
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Like, for example, product marketing.
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So, if you're a product marketing team, your goal is different.
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Maybe you're working with on the you are looking to draw in new leads or you're talking to customers and then you're talking to them about what's new and uh talk about your blog.
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There you give them a video and maybe a document.
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Then you have an implementation team.
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So the implementation team is taking a customer live.
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Now, when they take them live, most of the times what happens is that the implementation team configures the system based on the customer requirements.
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So, especially if you're a SaaS product with the numerous settings that you have, not every setting is enabled.
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You know, you add many features that are configured based on the customer's workflow.
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So the training that is given to them is specific to their context.
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And then after the training is done, maybe they give a video recording, or if the uh you know customer is okay paying money for it, they also get documentation.
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So, in this, they get document plus a video.
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Then, if you come to training, training again is the voice of the product, so it is the voice of the product manager, it is a generic training content where you're talking about the product's vanilla flavor and all the settings that are out there and how it can be used.
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But of course, when you are doing training, the objective is not to cram everything that you know into the video, it is about giving customers adequate information that they are familiar with how to use the product, they ease into the product, and then after the ease into the product, the next part comes in when they have further questions or when they want nuances.
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That is when they go to the help content or the help portal.
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So, over here, too, the deliverables that you give is a combination of videos and documents.
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Then comes in when a you know user is actually working in the product.
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If they are stuck, how do you help the customer navigate the tricky situation?
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Or how do you provide just in context help?
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That is where the DAP comes in, the digital adoption platform, platforms like WalkMe, Whatfix, Pendo, or Gainsight PX.
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So these sit on top of the product and give you contextual help.
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And if you're using, if you are a team which is in customer experience or change management, you are again giving customers uh customized resources, which are either documents or videos, or taking care of the DAP and providing context in help.
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So, long story short, now across multiple departments, you're talking about the same product, but how it is dressed up, how it is presented, at what detail, at what level, the granularity, it all changes based on the context.
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I think I drifted from the base question, but I was trying to lay out the fact that across multiple departments, when there are requirements for different teams, and all of this actually meet a common objective, which is to help customers succeed.
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I have been very fortunate that I was exposed to this in these wonderful companies where these founders, you know, they saw that you know this was a requirement.
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They gave me that opportunity to set everything up end to end.
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That gave me a lot of exposure and also got me a seat at the table where I was part of these conversations where how they were navigating the company to the next level.
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You mentioned that you got into companies that gave you that break.
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But then it's also important for a company to understand the value of content.
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Otherwise, this partnership would not be possible.
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So I think that's something that to me, that's what I take away from your journey, is that you were at the right place at the right time, but also you kind of made the right decisions.
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You were able to read what the company values about you.
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You're nodding your head.
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So I want you to add something to it, it looks like.
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Yes, I do want to add a point.
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Unfortunately, technical writers, for some reason, they prefer working in silos.
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They would just want to look at content in that silo.
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And uh, at least that's been my experience with many technical writers that I work with in India.
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I work with technical writers in the US and in UK as well.
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But as a tribe, we are very comfortable working in silos.
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Again, the reality is, at least working, having worked with multiple founders, now have spoken to over 200 founders over the last 12 months.
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I can tell you that if you walk up to a founder and you tell them that I will solve this problem for you, chances are that they are going to take a chance on you.
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So I will not say this happened naturally to me.
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It was also a culture that was in the organization where so one of my mentors is Anand Arvind, who is the co-founder of Zenoti. We were looking to hire a product manager, and then uh I I knew a person who was great.
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He was not a product manager before.
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He came from a sales background, but uh very technical, and I thought he could be a good fit.
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And I went up to Anand and I said, you know what, we are looking to hire a product manager.
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I think this person can be a fit, but he does not have product management experience before.
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So what do you think?
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He said, set up a discussion for me with him because you bought him up, I want to speak with him.
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And he proceeded to hire him.
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And I asked him, since you brought that person on board, he may not sure if you want to use him as a product manager, but can I may I understand it's you know what prompted you to select him?
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He said, Sagar, good people are hard to come by.
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So our philosophy is let's find the best people and then give them problems, tell them these are the problems.
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You take a choice, uh pick of what you want to solve.
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That kind of opened up my mind for me.
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So it doesn't need somebody to invite you and say, give me a problem, or how would they know that you know there is a burning desire in you, or you have some skill set that you'd want, you're capable of solving something.
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If you have to grow up in your career, or if you have to become an entrepreneur, you need to grab those chances.
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You very rarely would those chances be handed over to you in a platter.
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So you need to keep your eyes open.
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If you are looking at what a company needs right now, or what's the most pressing problem, and you align your goals or career objectives to that, and then you pitch and say, Hey, I want to try solving this.
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What's stopping anyone from giving you the chance?
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So the challenge that I see not only with technical writers but multiple people is they do not want to take no for an answer.
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They would, even if they go ahead and then they try once, and if they face rejection, they come back cribbing, saying that no one listens to me, rather than trying and figuring out why.
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So there is so much to things, it's like you know, if you are only it's difficult to explain in words, but if you have lived that experience.
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So it's basically there is so much nuance, there is so much context that you won't be prior privy to, and that is something that you have to earn.
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So I earned it by being persistent, I earned, I earned it by being diligent, I earned it by being detached to what I was doing. There were times when I would have spent days writing up something, and then you know, when the product manager told me, like, you know, this does not make sense or this does not seem right, and everyone has an instinct of they actually know if the other person is what the other person is saying, if it's making sense or not.
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So once you understand that, I have no problem discarding everything that I have done, putting it aside and starting afresh.
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So it is about learning while being detached.
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And if something negative comes your way, try and understand why the person said no and what is it that you're missing.
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And because you have put in that effort and that person has said no, now you have earned some stripes where you can talk to the person and ask what made you say no, and then you get to understand the nuances.
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If you're objective about it, you tend to become a bigger, uh, better person.
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So it's a journey that you need to get through.
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Especially, you know, I do not have a management degree, so there were many things that I learned on the job.
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There are things that life teaches you, and you there are instincts that you just built.
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And then in this day and age, finding right information is not difficult.
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So it is as simple as having conversations with the phone in your pocket, where Instagram or uh LinkedIn or any other algorithm that's listening on to what you're doing looks at it as a topic of interest.
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And as soon as you find some time in open social media or your LinkedIn, you're bombarded with all these uh messages.
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So it's like the entire universe conspires to present that information to you.
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Yeah, so that's what I wanted to add that it's not just being fortunate to be in a company that encourages, yes, I was fortunate.
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It's also your responsibility to take up the opportunity.
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you said that the universe kind of brought things together for you. Now, in my career, whenever I have tried to use videos, I've run into challenges.
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I kind of find alternatives to publishing content.
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Now, what problem kept following you that eventually convinced you to actually build a company around it and to actually solve that?
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Thank you for bringing up that question, Zohra.
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At Darwinbox and Zenoti, as I said, I was heading the customer education.
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And I had two departments with me.
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One was technical writing and the other was instructional designing.
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So while at Zenoti, first I set up the knowledge base and the help portal, then proceeded to create Zenoti University.
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And in Darwin Box, it was the other way around.
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What I did is I first created the videos, and then from those videos, I took the transcript and started creating documentation.
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Within 14 to 16 months, we were able to build out 2500 minutes of videos and over 1100 health articles.
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And this was a phase where there was no AI to help accelerate.
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It was the fact that I had exposure to multiple streams because these were SaaS platforms and not on-premise software.
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And we had progress from data writing to topic-based authoring, where it is more about how do you essentially achieve a certain particular task.
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It became easier because the video, the source video became an input for documentation and the writer needed to fill the gaps.
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So we were doing this, and videos as such was something that we invested a lot of money in.
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It doesn't come cheap.
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It's like if you're looking at a product video, it's not a marketing video.
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You don't need that ultimate finesse, you do not need the jazz that kind of blows you off your feet.
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You're coming in to understand what that particular feature does and how do you configure it.
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Now, even for this normal video to get it to work or to work with an agency or to build it in-house, a three-minute video working with an agency that I have worked for maybe a decade still costed a north of $150 per minute of published video.
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And it took us easily three to five days after we provided a transcript.
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So the transcript would be provided by my team or me, and then it would take three to five days for the vendor to turn it around.
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And then while I was at Oracle, after a release, we had at least 18 months before we could update our videos.
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We had that grace period.
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In a SaaS company, we had a leave of around 9 months, and it costed us as much money to update videos as it was to create them afresh.
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But by then, the videos, because most of the times what happens is I am joining a Series B company which has been around for five years.
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So there is five years of development.
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One, and then it started to do well.
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That means the product is usually exhaustive.
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You're catching up with a debt of five years, and then you are kind of figuring out what is the content that you need to first build, the 8020 rule.
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And then you're still trying to catch up, and you're still building out the newer features, but the features that have already built are outdated, and to update them, you need time from your team, and you also are working with the same vendor who's updating it, and you still uh you know you have to make it with the same budget year on year.
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So videos were something that everyone appreciated, everyone loves, but because there is a cost involved, because it is difficult to create, even a simple walkthrough video to make it polished, when you publish a video, there has to be a standard associated with it because it reflects your brand.
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So this was the challenge.
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It was expensive, time consuming, and uh you know, we couldn't keep up with the release.
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And then when AI came in, I thought now things should get better.
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Then I realized most of the AI tools, video AI tools, were focused on marketing, or they would talk about an avatar-based explainer video.
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But the tools that kind of said, hey, you know, if you currently talk to any organization, especially if you talk to a product manager or an instructional designing team, customer education, they would tell you almost 70 to 80% of their videos are a product walkthrough videos.
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Only 20% videos are those explainer videos.
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So I saw that there was a gap of tools that could actually help teams like us.
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I did find a couple of tools.
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To their credit, they were the first in the market and they did a pretty decent job to begin with.
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It still saved me 30 to 40% time.
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But only if you're an expert or if you do this at SCARE, you would understand that these tools are not built with you in mind. It so happened that what they built could also help us, but it was not built with the nuances of technical writing or nuances of instructional design.
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And then when I saw that there were not many tools around.
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And then I saw that there was this gap.
00:22:01.519 --> 00:22:15.759
I had actually given up on an entrepreneurial dream because two months before I decided I would start Zenious, my wife and I, you know, we went on a long drive and we uh you know we kind of decided, you know what?
00:22:15.759 --> 00:22:27.680
You know, let's we've been actually saving, you know, for uh for this phase of our life where I would invest money in starting my own company where we would not compromise on how we've been living our life.
00:22:27.680 --> 00:22:39.838
We thought we'll give ourselves two years, and we said, you know, nothing good's coming because most of the ideas that I had was kind of going and telling organizations that what you've been doing so far is wrong.
00:22:39.838 --> 00:22:44.000
Why don't you use my product or my idea to get it right?
00:22:44.000 --> 00:22:47.598
And I wasn't convinced myself that I would be able to sell it.
00:22:47.598 --> 00:22:51.358
So we decided that we would not do this at all.
00:22:51.358 --> 00:22:55.759
And then we went ahead and made some investments and we said that's about that.
00:22:55.759 --> 00:23:03.358
And a couple of months later, the idea of Zenious struck me, and I thought maybe you know, I'll just run it by my wife.
00:23:03.358 --> 00:23:06.720
And she just looked at me and she said, We should do it.
00:23:06.720 --> 00:23:12.558
And then if that wasn't enough, I approached Sandeep Choudri, who's my co-founder.
00:23:12.558 --> 00:23:17.519
He was an engineering leader at Microsoft, Microsoft Excel for web.
00:23:17.519 --> 00:23:24.318
He was pretty well placed, and uh, he's my friend, and you know, we were walking, and I said, I have this idea.
00:23:24.318 --> 00:23:25.440
What do you think?
00:23:25.440 --> 00:23:28.318
He stopped mid-track and he said, We should do it.
00:23:28.318 --> 00:23:29.519
He said, I'm on board.
00:23:29.519 --> 00:23:39.118
It was the time, it was the idea, and the right person to help me, where I had the domain expertise and he had the technical expertise.
00:23:39.118 --> 00:23:42.880
And we decided uh, you know, we'll take a plunge.
00:23:42.880 --> 00:23:49.759
It's I I can also let you on the story, what we did next after we decided we'll start a company, but I will late.
00:23:49.759 --> 00:23:51.200
Okay, you want me to continue?
00:23:52.078 --> 00:23:52.318
Please continue.
00:23:52.318 --> 00:23:52.880
Yes, absolutely.
00:23:53.519 --> 00:23:59.118
Sorry. The first thing after he said we will do it, we needed to be sure about two things.
00:23:59.118 --> 00:24:20.000
One, we needed undivided time between ourselves, where we peeled out every aspect of building a company, every aspect of the domain, every aspect of the challenges involved, and more importantly, while we have been friends, can we stand each other as business partners?
00:24:20.000 --> 00:24:29.440
So, what we did is we took off for a trek to Kedarnath and Badrinath for a week.
00:24:29.440 --> 00:24:38.240
It was just the two of us and the mountains where we were trekking the 15 kilometers, the 16 kilometers, just the two of us.
00:24:38.240 --> 00:24:50.400
And by the end of it, both of us were very convinced that yes, this is a product that's this is an idea that's viable, and we can work together because our mentalities match.
00:24:50.400 --> 00:24:58.558
Both of us, we have our own flair, and then, but at the core of it, the people uh who we are, it kind of is the same.
00:24:58.558 --> 00:25:02.400
So we thought, let's go ahead and do it, and we incorporated the company.
00:25:03.118 --> 00:25:04.240
That's such a cute story.
00:25:04.240 --> 00:25:04.960
Congratulations.
00:25:04.960 --> 00:25:11.759
So the universe did kind of come together, and I'm not saying that there was no initiative or effort from you.
00:25:11.759 --> 00:25:18.240
The idea germinated with you, but the fact that you kind of work towards it as well to make it happen.
00:25:18.240 --> 00:25:25.519
In sharing what you did, what I was also listening to was it is hard, no doubt, to create video content.
00:25:25.519 --> 00:25:29.358
I'm still kind of reluctant to do it.
00:25:29.358 --> 00:25:31.759
There is content that is the 80-20 rule.
00:25:31.759 --> 00:25:36.558
There is content that is good for videos, and there is content that is not good for videos.
00:25:37.358 --> 00:25:42.798
This episode is sponsored by LavaCon, the content strategy conference taking place this October in Charlotte, North Carolina.
00:25:42.798 --> 00:25:49.519
With more than 70 sessions and workshops featuring speakers from companies like Salesforce, TikTok, T-Mobile, and Amazon.
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LavaCon brings together content strategists, documentation leaders, and content professionals to share practical ideas you can apply right away.
00:25:57.358 --> 00:26:04.400
And yes, it's known as the Fun Conference, too, with networking events, therapy dogs, comfort llamas, storytelling, and karaoke.
00:26:04.400 --> 00:26:08.640
Use discount code ITC26 to save $200 on registration.
00:26:08.640 --> 00:26:16.558
In your opinion, what would be your advice to anybody that is considering videos and not thinking about it?
00:26:16.558 --> 00:26:18.000
How should they approach it?
00:26:18.000 --> 00:26:24.000
So that they can kind of move towards finding tools that can help them develop more content with videos.
00:26:24.000 --> 00:26:32.640
Because that's video is a preferred form of content consumption, but it's just so hard to, especially for documentation teams.
00:26:32.640 --> 00:26:34.558
So, what is your take on that?
00:26:35.358 --> 00:26:41.278
So if you are coming from a silo, you tend to bucket it as video and non-video.
00:26:41.278 --> 00:26:50.318
But what I would encourage you to do is not look at the format, but actually look at what you're trying to achieve.
00:26:50.318 --> 00:26:52.960
Like, let me give you an example.
00:26:52.960 --> 00:26:56.720
At Zenoti, it's a B2B business, right?
00:26:56.720 --> 00:27:01.440
So it's a company that builds software, believe it or not, for spas and salons.
00:27:01.440 --> 00:27:06.798
So the maximum users of the product are front-desk staff and the therapists.
00:27:06.798 --> 00:27:18.240
So while there is a 5 to 10% of the pro uh you know product that is used by businesses or the management, majority of the software is actually used by customers.
00:27:18.240 --> 00:27:25.759
So it's I would say for a B2B business, I had to create content for a B2B2C customer.
00:27:25.759 --> 00:27:37.200
Now, if they were to be trained, if they were to be onboarded, so we did the knowledge base, we had 1500 plus articles, but that wasn't sufficient.
00:27:37.200 --> 00:27:47.920
So, like for example, how can you expect someone, say if they are getting onboarded to Zenoti, to read a document and understand what needs to be done?
00:27:47.920 --> 00:27:56.000
So, but if that was accompanied by a video that they could watch, they get the nuances of how it is to be done.
00:27:56.000 --> 00:28:05.759
So you have a set of users who will need video guidance, and then you will have a set of users who will be setting it up or administering it.
00:28:05.759 --> 00:28:23.920
So the same philosophy also applies when you need to take a decision. So if you are creating content to help with onboarding, or if you want to see a reduction of support tickets because there are many how-to tickets coming in, then video is a format that can be preferred.
00:28:23.920 --> 00:28:39.278
But if while you are in your midst of your work, you need to surface some information, or you need to provide if somebody is configuring something and they need to understand the nuances how a particular field works, then having the text makes sense.
00:28:39.278 --> 00:28:47.118
But with Zenious, what we have been able to do is we it now gives you the flexibility where you don't have to choose.
00:28:47.118 --> 00:28:52.318
So what we have done with Zenious is that again I didn't speak about the USP of Zenious.
00:28:53.118 --> 00:28:55.680
The USP is we preserve your nuances.
00:28:55.680 --> 00:28:59.038
Now, how Zenious works is this way.
00:28:59.038 --> 00:29:02.798
Now, say you are a technical writer, you understand the feature end-to-end.
00:29:02.798 --> 00:29:13.680
Now, if you have to write a document or if you have to create a video, you need to spend time trying to figure out the storyboard, or you have to spend time you know structuring it.
00:29:13.680 --> 00:29:25.680
Of course, AI has made both of them easier, but the hard part of creating the video or editing the video, creating a video is not difficult, recording a video is not difficult, editing is the difficult part.
00:29:25.680 --> 00:29:37.920
So, what we have done is I understand the product video world, I understand the editing uh your people do when they're creating those videos, I understand how feedback is given.
00:29:37.920 --> 00:29:47.118
So, what we have done is we allow anyone who's a product expert or anyone at all, just speak naturally and record your screen.
00:29:47.118 --> 00:29:48.798
That is all you need to do.
00:29:48.798 --> 00:29:53.118
After you're done speaking and recording your screen, you just hit process with Zenious.
00:29:53.118 --> 00:29:57.680
Then what Zenious does is that it understands what you have tried to convey.
00:29:57.680 --> 00:30:00.640
We will ensure that we do not hallucinate.
00:30:00.640 --> 00:30:14.480
We will take what you have spoken, transcribe it, rewrite it, refine it, and make it professional while ensuring that the content is an accurate reflection of what you have spoken.
00:30:14.480 --> 00:30:18.640
And then to that narration or to that transcript, we add an AI voice.
00:30:18.640 --> 00:30:21.440
And then what we do is we take your video.
00:30:21.440 --> 00:30:35.200
Now, in the video, there will be loading screens, and there will be screens where you may not have spoken, there will be screens where you would have been distracted, and there would be screens where you have repeated the same information multiple times.
00:30:35.200 --> 00:30:37.680
So what we do is we take your transcript.
00:30:37.680 --> 00:30:52.240
Like for example, you may have recorded a four-minute video, but after we are done refining your narration and making it clear, it may just come down to 1 minute 30 seconds or 1 minute 40 seconds or 2 minutes, depending on how much you have spoken.
00:30:52.240 --> 00:30:57.838
Now that we take your video and then we edit out the video, the keyframes.
00:30:57.838 --> 00:31:21.920
We kind of take care of what needs to slow down, what needs to fasten up, and then we kind of sync your audio to the video, and then when we are done processing, which usually happens within minutes, you will see your video in a very polished format, and and that's covered the entire feature in a very crisp manner without losing your nuances.
00:31:21.920 --> 00:31:23.358
That's fun.
00:31:23.358 --> 00:31:30.400
And from the video itself, we still give you control where you go in and edit the transcript as you need.
00:31:30.400 --> 00:31:34.480
You do not worry about having to add voiceover again and sync narration.
00:31:34.480 --> 00:31:36.880
We automatically do it for you.
00:31:36.880 --> 00:31:41.038
You can after a video is processed, you can add as much information as you want.
00:31:41.038 --> 00:31:47.118
You could remove as much information as you want, and Zenious will sync the audio and video for you automatically.
00:31:47.118 --> 00:31:56.400
Now let's assume for a second, after you have recorded a video, say the UI changes, or say after the video is updated, uh your UI changes.
00:31:56.400 --> 00:32:01.278
I believe we are the only company right now which gives you a swap functionality.
00:32:01.278 --> 00:32:10.400
So what you can do is you can record only the portion of the video that has changed, and we have a transcript-based editor.
00:32:10.400 --> 00:32:15.118
You just select the transcript and say for this transcript, now use this video.
00:32:15.118 --> 00:32:20.160
So we retain your existing transcript and have changed the background video.
00:32:20.160 --> 00:32:25.278
So there are many other things, and from this video, we create a document.
00:32:25.278 --> 00:32:33.680
Now the document that we create, most of the tools out there they do screenshot, step, screenshot and step.
00:32:33.680 --> 00:32:36.798
But the content that we do is data-aligned.
00:32:36.798 --> 00:32:47.038
So we create a procedure element where you have a title, an introduction, a procedure subheading, and you would have a numbered list.
00:32:47.038 --> 00:32:50.960
And we actually know when to use a bullet list versus a numbered list again.
00:32:50.960 --> 00:32:57.598
You would have nested bullets and numbers along with screenshots, which is automatically generated for you.
00:32:57.598 --> 00:33:02.480
And the other USP is now we are creating this content from a video.
00:33:02.480 --> 00:33:08.480
Now, when you are creating a video, you have an audio queue and you also have a visual queue.
00:33:08.480 --> 00:33:17.278
Now, when you have these both, there are chances that you may not cover everything that is needed for a document.
00:33:17.278 --> 00:33:21.598
And if you are converting that into an article, it will seem incomplete.
00:33:21.598 --> 00:33:31.920
And that's why in documents, what we do is we allow AI to make some inferences as what you try to complete and what is the element that you may be clicking on.
00:33:31.920 --> 00:33:44.400
And after AI makes those inferences, we highlight them so that you as a writer know that these are the elements that you have not covered in your video narration, and AI has added for you.
00:33:44.400 --> 00:33:51.358
So at a glance you can see what AI has inferred, review it, accept it, or reject it.
00:33:51.358 --> 00:34:02.640
So we not only give you AI inferences and give you structured content, we also give you either a conceptual article, a troubleshooting article, or a blog post.
00:34:02.640 --> 00:34:10.639
Now, because I am from this background and it's a lived experience, one, I was able to put the nuance, uh, you know, the AI inferences together.
00:34:10.639 --> 00:34:18.320
Now, when you export it, you can export it as an HTML, you can export it as an XML, or you can export it as an RTF.
00:34:18.320 --> 00:34:34.159
Now, the challenge that happens is when you're exporting as an HTML or XML is that the images that are in there, usually you are required to have a separate base 64 folder, or you're required to download all the images and then keep pasting them separately.
00:34:34.159 --> 00:34:37.360
So in our platform itself, we give you an option.
00:34:37.360 --> 00:34:38.639
How would you want to do it?
00:34:38.639 --> 00:34:44.960
Do you want to download it as an images folder, or would you want us to embed as a base 64 when we export?
00:34:44.960 --> 00:34:49.518
So those are the nuances that we are able to capture within the product.
00:34:49.518 --> 00:34:56.079
Again, I just let you on to some of the decisions or how we have built Zenious, but there is much more to it.
00:34:56.559 --> 00:34:58.559
Is there a demo that one can watch online?
00:34:58.559 --> 00:34:59.280
Yes.
00:35:00.079 --> 00:35:06.480
So you know, you could go to help.zenious.ai and yeah, you would have anything that you would want to watch.
00:35:07.039 --> 00:35:07.760
You mentioned data.
00:35:07.760 --> 00:35:11.840
Now, what if a company does not use data, but they're doing topic-based authoring?
00:35:12.719 --> 00:35:19.760
It doesn't matter because even if it's topic-based authoring, it is always good for you to have it in a particular structure.
00:35:19.760 --> 00:35:32.159
So in this day and age where you need AI to be able to pick up information, you able to get content in a structured manner is actually a big plus for your AI.
00:35:32.800 --> 00:35:48.559
Right. So the follow-up question that I have is if I were using Zenious, and let's say I'm using MadCap Flare or any authoring tool, it is easy to hook it up and create a workflow that I could go from content to video.
00:35:48.559 --> 00:35:50.400
That's how I'm thinking about it.
00:35:50.960 --> 00:35:53.360
Actually, it's not from MadCap Flare to Zenious.
00:35:53.360 --> 00:35:56.079
It is about look at it this way.
00:35:56.079 --> 00:36:03.199
It's like, you know, uh Zenious will be the place where you are creating the source content and then you're exporting it to MadCap Flare.
00:36:03.199 --> 00:36:20.239
Oh, like for example, look at it like Paligo, where you are authoring content in Paligo and eventually publishing it to an S3 bucket, or you're authoring it, or you're publishing it to say Zoom, or you're publishing it to Fluid Topics, one of my favorite uh you know platforms.
00:36:20.239 --> 00:36:33.518
So here it's a platform that's allowing you to create that video and document, and then you are embedding that video into MadCap Flare, or you are exporting content from Zenious into MadCap Flare.
00:36:34.719 --> 00:36:37.119
So it is tools agnostic in a sense.
00:36:38.400 --> 00:36:39.679
Correct. Right? That's what I was trying to get at.
00:36:40.079 --> 00:36:52.719
Exactly. So look at us, like you know, if you use Canva or if you use Captivate or if you use Camtasia, you are creating a video and you're downloading it and you're using it wherever you want.
00:36:52.719 --> 00:36:58.239
In Zenious, also is the same thing that you could create, download, and use wherever you want.
00:36:58.719 --> 00:36:58.880
I see.
00:36:58.880 --> 00:37:03.760
Now, what happens if I have content that I want to create videos from?
00:37:03.760 --> 00:37:08.480
Because that is the more natural path from where I come.
00:37:08.480 --> 00:37:10.159
How would that work?
00:37:10.880 --> 00:37:25.280
So if you already have content that you want to create videos for, what you could do is you can just from say if you have a help article, and then all you need to do is give the help article to AI and say, create a script out of it.
00:37:25.280 --> 00:37:31.920
You have your script ready, then just follow your script and perform the screen actions without having to speak.
00:37:33.039 --> 00:37:38.159
Okay. Then what you do is use Zenious, upload your recording, upload your transcript.
00:37:38.159 --> 00:37:47.679
Zenious will take your transcript, will look at your video, and intelligently sync audio and video automatically without you having to do anything at all.
00:37:47.679 --> 00:37:49.599
And it will give you a polished output.
00:37:50.320 --> 00:37:54.800
The editing time that is definitely a challenge, and that's one thing that has kept me away from doing a video podcast.
00:37:54.800 --> 00:37:57.199
I've been asked why don't you do a video podcast?
00:37:57.199 --> 00:37:58.960
And it's it's syncing it up.
00:37:58.960 --> 00:38:02.239
Once I edit the audio, how do I sync it up with the video?
00:38:02.239 --> 00:38:03.440
It comes with high cost.
00:38:03.920 --> 00:38:04.559
Can I add something here?
00:38:04.559 --> 00:38:05.440
Yes, I can see.
00:38:05.440 --> 00:38:06.800
Yes, you're exactly right.
00:38:06.800 --> 00:38:16.079
What we have actually done with Zenious is we have automated the video editing, similar to articles, where you have multiple rounds of reviews.
00:38:16.079 --> 00:38:19.599
For videos, also, you have multiple rounds of reviews.
00:38:19.599 --> 00:38:21.440
You have at least three rounds of reviews.
00:38:21.440 --> 00:38:27.119
Earlier, you needed to build the video thrice to be able to get this done.
00:38:27.119 --> 00:38:32.800
So if you're if you are using Camtasia, then what you will need to do is you need to have a video separately.
00:38:32.800 --> 00:38:43.679
Then you need to have audio track created separately, put them in, start syncing them up, and then do the editing and then give a published output, which is going to take time.
00:38:43.679 --> 00:38:50.320
In Zenious, it is as simple as clicking edit on transcript, make the change that you want.
00:38:50.320 --> 00:38:54.719
Zenious automatically takes care of the editing without you having to do anything at all.
00:38:54.719 --> 00:38:55.280
Okay.
00:38:55.280 --> 00:39:00.320
And the way Zenious works is everything that you see is transcript-based.
00:39:00.320 --> 00:39:03.760
So this works great for a technical writer.
00:39:03.760 --> 00:39:17.599
Like for example, as a reviewer, I would uh on a video, I would actually put in a word, the document where I would add my comments where I would say, when the voiceover says this, until this show this highlight.
00:39:17.599 --> 00:39:23.440
Or when the voiceover is here, either you would tell the time or you would tell the voiceover text.
00:39:23.440 --> 00:39:24.800
We will say do this.
00:39:24.800 --> 00:39:27.840
So the same philosophy we carry forward in Zenious.
00:39:27.840 --> 00:39:32.000
So anything that you need to do in Zenious is from the transcript.
00:39:32.000 --> 00:39:39.039
Like for example, when the voiceover says click teams and group, you want to show a spotlight.
00:39:39.039 --> 00:39:43.280
So what you have to do is select the transcript, teams and groups.
00:39:43.280 --> 00:39:50.400
It will bring up a context menu, and then you say spotlight and place the spotlight.
00:39:50.400 --> 00:39:53.039
You don't have to work with the timeline at all.
00:39:53.039 --> 00:39:57.199
The effect will come in for the duration that you have selected on the transcript.
00:39:57.199 --> 00:40:00.800
Let's assume that AI has pronounced something incorrectly.
00:40:00.800 --> 00:40:07.679
You double-click on the word and say say as and enter the pronunciation that you want to add there.
00:40:07.679 --> 00:40:13.119
Or at a particular point in the video, you want to insert a chapter slide.
00:40:13.119 --> 00:40:22.320
You click on the word and say insert, and you could insert a slide directly without having to clip your video and add anything.
00:40:22.320 --> 00:40:33.599
So inserting a transition or inserting a video or inserting a slide is just a matter of selecting and inserting without having to do anything else.
00:40:33.599 --> 00:40:39.679
No need to edit your keyframes, manipulate your keyframes, or no need to do any clip management.
00:40:39.679 --> 00:40:40.800
So that's all automated.
00:40:40.800 --> 00:40:45.840
So you can say Zenious has automated, it's made the production very easy.
00:40:45.840 --> 00:40:53.679
So what now you'll be able to do is only focus on getting the right content out and leave the worry of editing to Zenious.
00:40:53.679 --> 00:40:54.639
Yeah.
00:40:54.639 --> 00:41:02.719
So you are very feel-free and you're welcome to sign up, go to zenious.ai and sign up for a free trial.
00:41:02.719 --> 00:41:06.559
You don't need to give a credit card, you don't need to give anything else.
00:41:06.559 --> 00:41:11.679
You have a seven-day free trial and create content as you want without a worry.
00:41:12.400 --> 00:41:16.639
What was the hardest technical problem to solve as you kind of set up Zenious?
00:41:16.639 --> 00:41:17.840
Were there any challenges?
00:41:17.840 --> 00:41:19.518
And if so, I would be interested.
00:41:20.559 --> 00:41:23.360
Yes. So the biggest challenge is the audio video sync.
00:41:23.360 --> 00:41:26.800
So it's like, you know, you need that intelligence to understand.
00:41:26.800 --> 00:41:30.880
Say it's like, you know, you say the voiceover goes like this.
00:41:30.880 --> 00:41:33.920
After you have set this up, you need to go and click save.
00:41:33.920 --> 00:41:35.518
Now proceed to click save.
00:41:35.518 --> 00:41:39.119
Now, at what point do you actually click on the button save?
00:41:39.119 --> 00:41:39.920
One.
00:41:39.920 --> 00:41:56.159
Second, say if you're actually looking at a UI element, which is a drop down, and you have not spent much time on it, we should be able to know like that is the space, place that you need to pause quite a bit for you to be able to internalize what's happening.
00:41:56.159 --> 00:42:03.518
We are an AI platform, but the LLMs don't do the video editing for us.
00:42:03.518 --> 00:42:24.960
So we have algorithms, we collect a lot of metadata from LLMs, which kind of tell us how Zenious should be working on a particular segment, when to slow it down, when to speed it up, all at the same time, where it's giving you a very consistent pace and you don't feel hurried.
00:42:24.960 --> 00:42:36.880
Unlike other AI platforms, when you look at AI voices and you're looking at the videos, the voices is running and the video is running as well, and it doesn't give you enough time to absorb.
00:42:36.880 --> 00:42:42.719
Now, our biggest victory was to able to get the sync working right.
00:42:42.719 --> 00:42:44.639
And we've been able to nail it.
00:42:44.639 --> 00:43:00.400
And again, I'm not saying that myself, it's our customers that we've been able to convert who have also been using platforms that have been around for at least two years, and they tell us uh with Zenious, they get content which is almost publication ready.
00:43:00.400 --> 00:43:07.920
So some of the customers who were using other platforms did a benchmark exercise of the same video.
00:43:07.920 --> 00:43:18.800
They used ours and they used our competitors, and in a three-minute video, they needed to adjust audio and video at least 14 times when they were with the competitor.
00:43:18.800 --> 00:43:21.760
And when it came to Zenious, it was not more than three.
00:43:21.760 --> 00:43:30.000
And even the time that is needed to sync in Zenious, it's hardly seconds because what we have is a what you see, what you get editor.
00:43:30.000 --> 00:43:37.679
So basically, you just select a word and say instead of this time frame, sync it to this time frame and you click apply.
00:43:37.679 --> 00:43:39.119
That is all you need to do.
00:43:39.119 --> 00:43:46.480
Unlike other platforms where you need to add sync points and then try and imagine if this is the right area and then do the syncing.
00:43:46.480 --> 00:43:55.280
So sync is one place where we have done extremely well, and that continues to be our USP because we are able to get production ready in one go.
00:43:55.280 --> 00:44:08.480
The other nuance, you know, which was a challenge, more than a challenge, I Would say which was very exhaustive for us is the fact that AI voices have multiple neural variations.
00:44:08.480 --> 00:44:16.719
Like for example, a voice in a Microsoft Azure can have as many 80 neural variations.
00:44:16.719 --> 00:44:22.719
Now, the default voices, not every voice is suitable for uh a product narration.
00:44:22.719 --> 00:44:30.159
So you need to understand which of these uh variations is suitable for product education, that is number one.
00:44:30.159 --> 00:44:36.320
And all voices, they also come with a default pitch and pace.
00:44:36.320 --> 00:44:54.480
And then based on the neural selection that you do, we have to manually, you know, we needed to understand, okay, one, what is good for product education, second, for the variation that we have selected, what is the pitch that is preferred and the pace that is preferred.
00:44:54.480 --> 00:44:58.480
Now we have thought into that granularity as well.
00:44:58.480 --> 00:45:06.559
So figuring it out, figuring it out how to use it, and then make it seamlessly work with our sync feature.
00:45:06.559 --> 00:45:14.480
Because depending upon the voice that you select, depending upon the pace that you select, the pace of the audio keeps changing.
00:45:14.480 --> 00:45:18.000
So you have to ensure that still continues to remain in sync.
00:45:18.000 --> 00:45:26.880
So getting them together, I would say, has been the biggest challenge. And also that's one of our very strong points because we've been able to do that well.
00:45:27.360 --> 00:45:34.719
Has building Zenious changed your own thinking about documentation, other assumptions you held a few years ago that you no longer believe?
00:45:35.679 --> 00:45:42.960
I think it has more than ever reinforced the belief that documentation is very integral to organizations.
00:45:42.960 --> 00:45:50.639
So for AI to work effectively, you need now need to have a very robust knowledge layer.
00:45:50.639 --> 00:45:55.360
So many companies now are building contextual brains.
00:45:55.360 --> 00:45:59.518
And if you look into those brains, it is all structured content.
00:45:59.518 --> 00:46:02.559
About it has a map of your entire product.
00:46:02.559 --> 00:46:10.639
It not only has a map of your entire product, and within that, for each feature, it has contextual information about how that feature works.
00:46:10.639 --> 00:46:14.000
Now, see, you have to look at it from two lenses.
00:46:14.000 --> 00:46:23.360
One, there is native AI companies, where the entire from ground up, AI has played a key role, including creation of documentation.
00:46:23.360 --> 00:46:32.559
And there are companies which have dominated the market for a long time and AI is bolted on top of them, and then you know they are continuing to exist.
00:46:32.559 --> 00:46:42.960
In both these cases, you would see, for example, if you take Anthropic or if you take Cursor, they do have roles for customer education.
00:46:42.960 --> 00:46:45.199
They have roles for technical writing.
00:46:45.199 --> 00:46:46.880
And why is that?
00:46:46.880 --> 00:46:53.518
So if this field wasn't relevant, you know, they wouldn't be having those roles, number one.
00:46:53.518 --> 00:46:58.400
And number two, is with AI, what's important?
00:46:58.400 --> 00:47:01.599
Let me just take a step back and lay it out for you.
00:47:01.599 --> 00:47:09.840
As I see it in the current day and age, AI has uh had an impact on almost every role.
00:47:09.840 --> 00:47:23.039
Like, for example, let's take a business development BD, for an example, who's putting out together content for management to take a decision as how they should be going.
00:47:23.039 --> 00:47:31.039
Now, if you see the end content that is handed over to management, the BDE is still building it.
00:47:31.039 --> 00:47:48.880
But the BDE is leveraging tools to be able to build that content faster, to understand the nuances faster, and present it to management. It's not that man, you know, people in power do not have the capability to do the research themselves and extract that information.
00:47:48.880 --> 00:47:51.679
They could do that before, but still they had a BDE.
00:47:51.679 --> 00:47:54.960
They can do it now and they have AI, they'll still leverage a BDE.
00:47:54.960 --> 00:48:05.840
The point that I'm trying to get to is that AI is accelerating the content creation part where intelligence has become a commodity.
00:48:05.840 --> 00:48:24.800
So it's able to give you so many facets of different aspects and nuances, it requires a human judgment to kind of understand what is relevant for your company from your context and from your business.
00:48:24.800 --> 00:48:27.199
So that's not going away anywhere.
00:48:27.199 --> 00:48:32.079
I think I know where your question is coming from in the context of technical writers.
00:48:32.079 --> 00:48:44.000
But the reality is if you're looking at a development team, it has developers, it has product managers, it has QA, it has UX, right?
00:48:44.000 --> 00:48:45.039
UI and UX.
00:48:45.039 --> 00:48:49.039
Now, you would say creation of content is easy.
00:48:49.039 --> 00:48:50.480
It has become easier.
00:48:50.480 --> 00:48:55.199
But would a product manager prefer doing the documentation?
00:48:55.199 --> 00:48:59.039
Would a developer prefer doing the documentation?
00:48:59.039 --> 00:49:01.039
The answer is no.
00:49:01.039 --> 00:49:11.039
So it still comes down to a specialized role who understand the nuances, understand the structure, and then you know, that's not going anywhere.
00:49:11.039 --> 00:49:12.400
That's how I say it.
00:49:13.039 --> 00:49:16.639
Content generation has definitely become accelerated, no doubt.
00:49:16.639 --> 00:49:17.119
Yeah.
00:49:17.119 --> 00:49:31.679
But how do we as humans kind of keep that perspective in mind that, like you said, there is a context to the company, to the product that you're working for, working in, and that is not going away.
00:49:31.679 --> 00:49:35.039
And I think that's where our biggest advantage is. Yes. Right?
00:49:37.599 --> 00:49:38.000
That's correct.
00:49:38.000 --> 00:49:43.280
But while that's not going away, if you change nothing, nothing will change.
00:49:43.280 --> 00:49:47.760
So what you need to do is you need to understand the new reality.
00:49:47.760 --> 00:49:51.840
The new reality is the boundaries have shrunk.
00:49:51.840 --> 00:49:57.840
Now, even a developer is now able to use cloud design to create UX.
00:49:57.840 --> 00:50:03.199
A product manager is able to do documentation, they're able to generate videos.
00:50:03.199 --> 00:50:12.800
So the ability for someone to create good-looking content or good-looking UI or UX, that's not going away.
00:50:12.800 --> 00:50:19.760
But where this will become, where technical writers can come in, is they can become the knowledge orchestrators.
00:50:19.760 --> 00:50:27.840
So across multiple departments, across a customer journey, you have multiple pain points.
00:50:27.840 --> 00:50:39.599
As I kind of mentioned earlier in the show, that across departments, it comes down to two content artifacts, which is a video and which is another is document.
00:50:39.599 --> 00:51:15.760
Now technical writers can become that orchestrators where they are able to maintain a single source of truth and present this information at strategic places using delivery mechanisms, which can either be a help portal, it can be a knowledge base, it can be a DAP, it can be an LMS, and present content in a format or dress up content in a format that is useful for a customer in at that particular step or their phase of journey.
00:51:15.760 --> 00:51:19.440
So that is where I see the biggest USP for writers is.
00:51:20.159 --> 00:51:27.039
Yes. I think how I'm gonna interpret this is you use the phrase dress up, and I'm a little hesitant to use that.
00:51:27.039 --> 00:51:33.518
Everybody thinks, when I say everybody, the stakeholders that technical writers work with think we edit.
00:51:33.518 --> 00:51:35.760
We are given the content and we edit.
00:51:35.760 --> 00:51:38.719
So the dress up in that context is oh, we'll be editing.
00:51:38.719 --> 00:51:46.000
No, I think you had something much more valuable to bring, thinking of how is the customer going to consume that content.
00:51:46.000 --> 00:51:48.719
That is so critical because nobody else is thinking about it.
00:51:48.719 --> 00:51:54.960
And then you kind of match that pace, match that wavelength, match that requirement, that judgment.
00:51:54.960 --> 00:51:59.199
So there is a science to it, and that's where we can bring our value.
00:52:00.079 --> 00:52:02.480
True. Uh, I agree with you completely in that context.
00:52:02.480 --> 00:52:13.280
But again, I would think not just technical writers, uh, with in the new age where AI is doing most of the development, isn't everyone becoming an editor of sorts?
00:52:13.280 --> 00:52:27.518
So when I meant dress up, uh, you know, it could have been interpreted incorrectly, but the meaning was be it a developer, product manager, or a UX designer, or a technical writer.
00:52:27.518 --> 00:52:33.280
Earlier the challenge was how do you create content that catches up with your product?
00:52:33.280 --> 00:52:37.599
Now, with AI, there is so much content that is being generated.
00:52:37.599 --> 00:52:45.199
It is about deciding what goes in and what goes out or what remains. So I came from that sense.
00:52:45.840 --> 00:52:47.920
We are at time and I want to respect that for you.
00:52:47.920 --> 00:52:49.920
Anything else that you would like to add?
00:52:50.480 --> 00:52:52.320
So actually, there is a lot to unpack.
00:52:52.320 --> 00:52:54.800
There are many things that I'd love to share.
00:52:54.800 --> 00:53:05.199
But to end with, I would like to say that I think there has never been a better time for a content person than now.
00:53:05.199 --> 00:53:26.880
So while it may seem on the contrary, but I do believe we are going through a phase where from discovery of how AI can help us to actually running experiments to leverage AI to deliver features to a phase where now with AI you've been able to build more features faster.
00:53:26.880 --> 00:53:32.960
And then historically, like for example, I'm just going to take DVT error for a second.
00:53:32.960 --> 00:53:40.719
Now, if you took a signup with SAP, you needed to wait years before implementation could be done for you.
00:53:40.719 --> 00:53:50.639
If you raised a feature request, even with a startup, it would take you quarters before the feature would actually make it to the roadmap or even if they would consider it to uh in the roadmap.
00:53:50.639 --> 00:54:00.000
The fact is that businesses, what they need, are usually ahead of where your software is.
00:54:00.000 --> 00:54:04.559
So software has always played catch-up with what the business required.
00:54:04.559 --> 00:54:15.119
And as and when you start feeding that engine, if you're able to meet the requirements of what a business means, business will always find newer needs.
00:54:15.119 --> 00:54:18.079
It will find newer ways to grow.
00:54:18.079 --> 00:54:20.639
And then that cycle does not stop.
00:54:20.639 --> 00:54:24.559
So I would say this is a phase where things are getting consolidated.
00:54:24.559 --> 00:54:44.400
And now that we know that we can get outcomes from AI, and we are also figuring out how we can leverage AI better, and teams are adjusting to a world in a uh you know with AI, it's only a matter of time where there is more business that is generated.
00:54:44.400 --> 00:54:47.920
And when that happens, you will need more people.
00:54:47.920 --> 00:54:50.960
So I don't see that going away.
00:54:50.960 --> 00:54:57.920
I see that you know you will need all roles, not just fighters, but you'll be working in a different manner.
00:54:57.920 --> 00:55:00.719
You will be able to get more done than less.
00:55:00.719 --> 00:55:07.518
What I will disagree with is the statements that AI is supposed to free you up.
00:55:07.518 --> 00:55:09.280
I don't think uh that's the case.
00:55:09.280 --> 00:55:17.599
I see people working more than ever, harder than ever, than before, because you're able to get more things done, but it's good for business.
00:55:17.599 --> 00:55:19.760
And if it's good for business, it's good for you.
00:55:20.320 --> 00:55:23.679
On that note, Sagar, thank you so much for coming on my show.
00:55:23.679 --> 00:55:26.320
I appreciate it and I appreciate this entire walkthrough.
00:55:26.320 --> 00:55:29.440
And stay tuned, I will be checking it out.
00:55:29.440 --> 00:55:30.320
Thank you so much.
00:55:30.800 --> 00:55:31.518
Thank you so much, Zara.
00:55:31.518 --> 00:55:32.400
My pleasure.
00:55:33.920 --> 00:55:36.000
Thank you for listening to Inside Tech Comm.
00:55:36.000 --> 00:55:40.559
If there's a guest you would love to hear on the show, please let me know.
00:55:40.559 --> 00:55:45.840
And don't forget to follow and catch every episode on your favorite podcast app.
00:55:45.840 --> 00:55:47.199
See you next time.