رونوشت 🔗
WEBVTT
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It's very easy to prompt an AI to to do
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something if you're willing to accept a
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level of error. If you get your entire
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app designed by Claude, it will sort of
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iterate its way into something very ugly
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and that that's not maintainable.
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So, Ryft is the UK answer to Stripe and
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Adyen.
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You told Business Insider that the Ryft
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has already broken even your 2025
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accounts at company's house show losses
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grew by 1.8 million. So, are you guys
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profitable at the moment?
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No.
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Barclays is cutting 5,000 jobs and it
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says AI is part of the reason. Really,
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AI or just cost cutting with AI label on
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it.
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The CEO of Barklay is on the call said
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AI is the icing on the cake, but it's
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not the actual cake.
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Tens of thousands of attacks attempts in
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the first 45 minutes and millions by
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that evening. if AI can find the [music]
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bugs that's been there for 10 years and
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I want to know how many more out there.
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Does AI make the internet safer or more
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dangerous?
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Welcome to another episode of On the
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Ground Podcast. We brought to you a lot
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of breaking news this week and also we
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have a line of super interesting guests
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on this episode of On the Ground
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Podcast.
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But apart from that Sam, you had quite a
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busy week, haven't you? What have you
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been up to?
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Yeah, it's it's been a really really
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busy week. Yesterday at midnight, I
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landed back in London from uh Berlin, I
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was at Nvidia GTC event. Um had finally
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chance to meet Jensen in person. We had
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a nice keynote session where he taught
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some robots how to act, what to do. It
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was really fun. And also uh we had a
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nice Q&A session um the next day. Um and
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I can see that Nvidia is bringing a lot
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into the UK and European market. And one
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thing that stood out for for me was
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particularly the OpenShell framework,
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open-source framework that they are
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bringing to basically we covered this
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autobe it is to contain rogue um AI
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agents from going out and breaking into
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other systems. And um I believe this is
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one of the best tools particularly for
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banks and financial institutions because
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you have to be careful with customer
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funds. You cannot simply allow AI um to
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do whatever you it wants. Um and also we
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know that the industry is very very
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regulated and also I think
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yeah tell me
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well I hope you convince Jensen to come
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on our show and share that experience
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directly with our audience.
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Right. Yeah. Yeah definitely. I think
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hopefully hopefully yeah the the first
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uh milestone is already set achieved. Uh
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I did a selfie with Jensen which was
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good and then
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yeah it is it is and the next one
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hopefully we will definitely at one
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point have him on our podcast and learn
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more what they are building um not only
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in Europe or the UK but overall globally
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but so far um they are doing really
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really great job. Well, uh, now let's
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bring in our guests and let's discuss
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some of the latest breaking news and get
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their opinion. Today we have James
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Broadhead on the ground with us today.
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James is the chief technology officer of
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Taktile. Uh, it's a company that helps
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banks, fintex, and insurance companies
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use AI to decide who to get loan, which
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payments are fraudulent, and which
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claims need to be settled. James joined
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recently from datab bricks after he led
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engineering at neon. Welcome James.
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Thanks great to be here
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James it's
Load full transcript
great to have you on the
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show. Um you joined Taktile literally
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last month in September and so you are
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coming from datab bricks and your
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background is primarily in working on
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database and data companies. So what do
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you bring to Taktile and why move um to
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decision level um in in the whole flow?
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Sure. Yeah. Um I guess so I think I'm
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joining Taktile at a really exciting
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time. So not only have models gotten
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exceptionally better in the last 12
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months. uh Taktile has a a platform in
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production on which we can build these
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agents and so we can me we can put the
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production readiness of the platform and
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the exciting new model developments
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together and build something really
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exciting. Uh you're right that my my
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background originally is in data
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databases. I fell in love running
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databases at Twitter uh we're running
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highcale systems there uh went into
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in the transition from onrem to
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cloud and then neon which was a
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Postgress startup um before being
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acquired by data bricks. But really the
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thing I enjoyed was that it was the
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hardest part of the stack operationally.
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So uh big databases are hard to
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maintain. Uh it's a high expertise
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system and and that's the the
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challenging thing and there were a lot
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of really interesting developments in
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databases over that time. But if you
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look at where the market's gone in the
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last sort of couple of years, it's all
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AI, right? Um and running AI and in
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particular making high quality decisions
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with AI is is really difficult. And so
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in the first half of the year at data
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bricks uh I spent the time sort of
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integrating our our technology into the
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company and the second half I um I was
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working on aentic coding and you'll if
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you look at their um their releases sort
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of around data bricks apps in the last
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year that's some of the stuff I was
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working on and as I got there it's I
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found that it's very easy to prompt an
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AI to to do something if you're willing
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to accept a level of error right but
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then the really interesting word becomes
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when you want to make sure that every
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time the customer uses the AI, they get
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the kind of response they expect or
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there's like a reliable um failure mode
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in which it passes out to a human team
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and it accepts that it's uh it's unable
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to make a decision for whatever reason
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and it reliably passes out to a human in
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the loop. So that's one of the the key
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details of of Taktile that I think is
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really interesting is the ability to to
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pass to the human team who have tons of
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domain and business expertise uh to
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record the outcome of that decision from
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the human team and pass that into the
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learning loop back into the next round
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of decisions. Um and so that's one of
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the really interesting problems that
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brought me to Taktile. James, um, if we
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were to look more on what happens under
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the hood, uh, in Taktile, let's say
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Semini, we are running a small business,
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we apply for a loan at Monzo who uses,
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uh, Taktile. What happens like if you
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break it down to a not non-technical
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audience?
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Yeah. So, I mean, this is probably easy
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if we if we go back a few years um, and
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we think sort of the the pre-automation,
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pre-AI world, applying for a loan, you
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submit a bunch of paper forms. those
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eventually land on someone's desk,
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whether that's as an email or PDF um or
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in an online tool. A human reviews that
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against a set of rules that are
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described in both uh the the kind of
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loan you're trying to get, the bank's
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own policies um and like a level of risk
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the the bank is willing to make in terms
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of how well does your application
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conform to those policies that bounces
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around inside the bank. Let's say it's a
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mortgage rather than a small scale loan.
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and a mortgage can be operated in an
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order of weeks at the moment. Right now,
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we've automated that. That's all a bunch
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of PDFs. We can pass those through OCR
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optical character resolution and then
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pass it to an agent. Uh we've given the
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policy PDF to the agent and there's a
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very there's a strict deterministic
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decision flow that the the claim will go
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through. That's a deterministic decision
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flow, but at some point in that model,
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it hits an a an agent that gets to make
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non-deterministic decisions based on the
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policies of your bank. Um, and based on
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maybe the the circumstances of the
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particular week. Uh, maybe the markets
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are good, we're willing to make a
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slightly more risky loan. Maybe the
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markets are bad, we're going to make
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we're going to we're going to dial the
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risk back down. But either way, there is
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a a fixed policy that's in place from
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the business. Then there's a controls
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from the business users uh that
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determine sort of based on today's
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business scenario, how do we want these
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flows to work? And right there in the
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middle of the flow is an agent making
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decisions based on the inputs it being
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given both the like the hard rules and
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the um the softer rules.
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Um and then it'll output a
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recommendation.
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James, uh by the way, congrats. Um you
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guys raised $110 million in June. Um now
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since you are a CTO at the company how
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are you planning to spend that money in
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terms of engineering and software
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development?
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Yeah um really I mean uh getting the
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series C is a huge accomplishment by the
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team. I'm really pleased for them and I
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think it it says a lot about about the
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health of the company and the success of
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the platform and in particular one of
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with the invest the main investor being
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Goldman. I think that says a lot about
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their confidence in Taktile in march
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into banking. So I think Taktile has has
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a lot of uh sort of new bank neo bank
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customers uh fintexs um but the future
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of the company is in enterprise and so
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with with Goldman's uh support we're
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sort of we're now opening doors into the
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largest enterprises in the world. I
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think one of our largest customers is
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Aliance. Um there's a big profile of
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them on the on the page but we're
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heading into Wall Street um in a serious
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way. I think there's two things we need
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to do to succeed in enterprise. One is a
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very standard enterprise journey where
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we we harden things sort of role-based
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access controls, networking limits, all
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those kinds of things. But the second
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thing is is differentiating features. Um
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and there what we look at in enterprise
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is the hard separation between um what
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the technical teams are looking for and
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what the business users need. And so we
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want to make sure that it's easy for an
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enterprise security or IT team to deploy
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Taktile with the hard rules that govern
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how Taktile should work in general, but
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then to leave flexibility for the
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business users to bring in that business
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context, their understanding of sort of
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the market and the particulars of a
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given week or time and to tweak things
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as they go. and then for them to set
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ranges um inside of those those
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parameters
and for our system to learn
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through operation where that slider
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should be inside of the rules it's being
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given.
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Okay,
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there we have like a reinforcement
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learning loop. Um and that's how we will
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we tweak the decision making for the
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customers.
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James, you you mentioned Allianz
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Partners. Uh they say that 30% more
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health claims now goes through you guys
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with no human involved. Do you see that
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percentage increasing to even 100% uh
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and what the people are still checking
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at the moment?
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Yeah, so I think it it can be brought to
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100% but what it really comes down to is
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what the business is trying to achieve.
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So um for claims processing in a in a
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regular week within SLAs's you can have
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a fix team working and hitting SLAs's
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fine. Uh what what some of our insurance
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customers find though is exceptional
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events come in uh such as a severe
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change in the weather uh which
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dramatically change claims volumes
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there. They have the decision about
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either pulling in more team members to
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hit timing SLAs's or by automating more.
00:11:23.440 --> 00:11:24.640
And those are the two main decisions
00:11:24.640 --> 00:11:27.120
they have to make more by dropping the
00:11:27.120 --> 00:11:28.720
quality of the checks they're doing. So
00:11:28.720 --> 00:11:30.399
you can speed up a human team by giving
00:11:30.399 --> 00:11:33.040
them less work um or by bringing in more
00:11:33.040 --> 00:11:35.279
people. Um, those are all very expensive
00:11:35.279 --> 00:11:37.040
decisions. So, if you're willing to drop
00:11:37.040 --> 00:11:38.560
quality, you make payouts when you
00:11:38.560 --> 00:11:40.079
shouldn't. If you're pulling in more
00:11:40.079 --> 00:11:41.360
team members, you have to pay for that
00:11:41.360 --> 00:11:43.600
human time. So, what we're giving is a
00:11:43.600 --> 00:11:46.480
third option is spend more tokens. And
00:11:46.480 --> 00:11:48.160
generally speaking, token spend is
00:11:48.160 --> 00:11:50.320
expensive, but it's not as expensive as
00:11:50.320 --> 00:11:53.440
people. And so, we have a a detailed
00:11:53.440 --> 00:11:55.040
sort of analysis as part of Taktile
00:11:55.040 --> 00:11:57.440
Labs. We have a paper up talking about
00:11:57.440 --> 00:12:00.399
the quality of results, the time taken,
00:12:00.399 --> 00:12:02.959
the token spend, but comparing that
00:12:02.959 --> 00:12:06.079
against human decision-m time. Um, and
00:12:06.079 --> 00:12:09.279
so in terms of both pay and timing, uh,
00:12:09.279 --> 00:12:11.120
we find that's a really valuable third
00:12:11.120 --> 00:12:14.399
option for companies to have. So, you
00:12:14.399 --> 00:12:16.399
know, sitting at 30% today, they could
00:12:16.399 --> 00:12:17.600
make the business decision to try and
00:12:17.600 --> 00:12:19.760
move that to 35%.
00:12:19.760 --> 00:12:21.920
What we give them is the ability to
00:12:21.920 --> 00:12:23.760
replay the decisions from the last week
00:12:23.760 --> 00:12:26.160
or last month assuming they wanted to
00:12:26.160 --> 00:12:28.160
automate further and to see what the
00:12:28.160 --> 00:12:30.560
outcomes of that would have been. And
00:12:30.560 --> 00:12:32.399
that's the short-term outcomes in terms
00:12:32.399 --> 00:12:34.639
of the decisions they make today. But we
00:12:34.639 --> 00:12:37.680
also take like final outcome decisions.
00:12:37.680 --> 00:12:40.079
So for instance, in a loan case, we get
00:12:40.079 --> 00:12:42.399
to see over the months whether the loan
00:12:42.399 --> 00:12:44.160
was actually repaid by the person we
00:12:44.160 --> 00:12:46.560
granted the loan to. And so with that
00:12:46.560 --> 00:12:49.040
data we say on the day of the loan we
00:12:49.040 --> 00:12:50.639
knew this much about the person and we
00:12:50.639 --> 00:12:53.360
made this decision but 12 months later
00:12:53.360 --> 00:12:55.200
we now know that that person repaid and
00:12:55.200 --> 00:12:58.000
this one this person didn't. So that all
00:12:58.000 --> 00:12:59.680
goes back into the system in terms of
00:12:59.680 --> 00:13:02.079
ramping decision quality and giving the
00:13:02.079 --> 00:13:04.399
ability to ramp automation and actually
00:13:04.399 --> 00:13:06.399
increase quality and make fewer mistakes
00:13:06.399 --> 00:13:09.040
as opposed to uh to a human team that
00:13:09.040 --> 00:13:10.480
constantly needs retraining and
00:13:10.480 --> 00:13:12.800
expansion. James, most of the things
00:13:12.800 --> 00:13:15.200
that you guys are doing um goes around
00:13:15.200 --> 00:13:18.320
decision making, right? Um and when it
00:13:18.320 --> 00:13:19.920
comes to decision- making, we know there
00:13:19.920 --> 00:13:22.800
is bias. There is always bias even with
00:13:22.800 --> 00:13:25.360
with AI. Um because again, let's say the
00:13:25.360 --> 00:13:27.839
company has XY Z policy and the uh
00:13:27.839 --> 00:13:29.839
basically AI will follow those policies.
00:13:29.839 --> 00:13:32.240
How do you guys ensure that there is no
00:13:32.240 --> 00:13:35.120
bias and everyone is treated equally and
00:13:35.120 --> 00:13:37.839
AI also I mean treats uh applicants
00:13:37.839 --> 00:13:40.079
equally based on let's say their income
00:13:40.079 --> 00:13:43.120
and etc. but will will not go to other
00:13:43.120 --> 00:13:46.240
elements that uh could uh bring the
00:13:46.240 --> 00:13:49.440
results uh eventually uh relate to bias.
00:13:49.440 --> 00:13:50.959
Yeah, that's a really interesting
00:13:50.959 --> 00:13:53.680
question and one I'm not quite ready for
00:13:53.680 --> 00:13:57.040
at day 45 at the company. Uh thinking
00:13:57.040 --> 00:13:59.680
about it though, that's a that's a I
00:13:59.680 --> 00:14:01.519
think what we've learned in software
00:14:01.519 --> 00:14:04.079
engineering is we've done a lot of the
00:14:04.079 --> 00:14:05.920
automation of the software development
00:14:05.920 --> 00:14:08.240
life cycle. What we're finding as we go
00:14:08.240 --> 00:14:10.880
from trying to um take the basic work of
00:14:10.880 --> 00:14:12.399
a software engineer, implement this
00:14:12.399 --> 00:14:14.399
picket and then produce an outcome, that
00:14:14.399 --> 00:14:16.720
part's actually quite easy. The harder
00:14:16.720 --> 00:14:19.600
part is applying higher level judgments
00:14:19.600 --> 00:14:21.360
to the quality of the work. Whether
00:14:21.360 --> 00:14:23.120
that's in terms of like longer term
00:14:23.120 --> 00:14:25.600
engineering health of the codebase or in
00:14:25.600 --> 00:14:27.120
terms of product thinking about where
00:14:27.120 --> 00:14:28.880
you want the product to go rather than
00:14:28.880 --> 00:14:30.800
going step by step, brick by brick
00:14:30.800 --> 00:14:32.959
randomly, uh you want it to follow some
00:14:32.959 --> 00:14:35.120
kind of product strategy. And and
00:14:35.120 --> 00:14:37.360
thirdly in terms of design uh where if
00:14:37.360 --> 00:14:39.279
you get your entire app designed by
00:14:39.279 --> 00:14:41.360
claude it will sort of iterate its way
00:14:41.360 --> 00:14:43.040
into something very ugly and that that's
00:14:43.040 --> 00:14:46.639
not maintainable. And so if I apply that
00:14:46.639 --> 00:14:50.000
sort of second level of review idea to
00:14:50.000 --> 00:14:52.240
my codebase what I do is I have one
00:14:52.240 --> 00:14:55.120
coding agent separate to that I have a
00:14:55.120 --> 00:14:56.959
product agent that understands our
00:14:56.959 --> 00:14:59.199
product strategy. I have a design agent
00:14:59.199 --> 00:15:01.040
that understands our design strategy.
00:15:01.040 --> 00:15:03.360
and all of them look together at work
00:15:03.360 --> 00:15:04.800
we've been doing and make their own
00:15:04.800 --> 00:15:07.040
judgments with separate context and
00:15:07.040 --> 00:15:08.880
separate uh vetoing power over the
00:15:08.880 --> 00:15:10.160
decision-m
00:15:10.160 --> 00:15:11.199
okay
00:15:11.199 --> 00:15:13.519
if a customer came to me and said how do
00:15:13.519 --> 00:15:15.199
I build a flow and make sure it has
00:15:15.199 --> 00:15:17.760
limited bias I think what I would advise
00:15:17.760 --> 00:15:20.720
them to do is build an antibbias agent
00:15:20.720 --> 00:15:23.600
and say looking at this decision history
00:15:23.600 --> 00:15:25.120
looking at these these incoming
00:15:25.120 --> 00:15:29.120
customers um are we like systemically
00:15:29.120 --> 00:15:30.560
are we making decisions that that
00:15:30.560 --> 00:15:32.480
demonst demonstrate bias or that don't
00:15:32.480 --> 00:15:34.399
and what counterveiling signals can we
00:15:34.399 --> 00:15:35.760
put into that reinforcement loop to
00:15:35.760 --> 00:15:38.000
avoid it. I think that would be a really
00:15:38.000 --> 00:15:39.760
interesting engagement and I would love
00:15:39.760 --> 00:15:41.519
to be part of that. Um I've worked on
00:15:41.519 --> 00:15:43.920
debiasing projects at previous companies
00:15:43.920 --> 00:15:46.320
um but I I that customer haven't come to
00:15:46.320 --> 00:15:48.880
me me personally yet uh but I'd love to
00:15:48.880 --> 00:15:49.920
work together if one of them are
00:15:49.920 --> 00:15:50.399
listening.
00:15:50.399 --> 00:15:53.279
As you know on our show we uh analyze
00:15:53.279 --> 00:15:56.240
the news uh within the tech and industry
00:15:56.240 --> 00:15:59.120
and um give our take or guest take on
00:15:59.120 --> 00:16:00.880
them. One of the news that caught our
00:16:00.880 --> 00:16:02.560
attention last week was coming from
00:16:02.560 --> 00:16:05.120
Plate. They launched their own credit
00:16:05.120 --> 00:16:07.519
scoring uh service last week. Do you
00:16:07.519 --> 00:16:09.199
think I know that you guys work with
00:16:09.199 --> 00:16:12.480
with plate as well? Will that create a
00:16:12.480 --> 00:16:14.399
kind of a comp competition spirit
00:16:14.399 --> 00:16:16.560
between Taktile and and plate? Uh what
00:16:16.560 --> 00:16:17.759
is your take on that?
00:16:17.759 --> 00:16:20.000
Well, I think it's always interesting
00:16:20.000 --> 00:16:22.240
when there are competitors because it
00:16:22.240 --> 00:16:23.839
means you're in a market that multiple
00:16:23.839 --> 00:16:25.920
people have identified and it it sort of
00:16:25.920 --> 00:16:28.160
validates the the the hypothesis of
00:16:28.160 --> 00:16:30.800
where you're going. Um, I'm not scared
00:16:30.800 --> 00:16:32.320
of competition. I think you can learn a
00:16:32.320 --> 00:16:34.240
lot competing for the same customers and
00:16:34.240 --> 00:16:36.240
seeing how decisions go. Uh, I think
00:16:36.240 --> 00:16:37.600
it's always good to be able to compare
00:16:37.600 --> 00:16:40.399
yourselves to competition. Um, I think
00:16:40.399 --> 00:16:44.079
there are areas in which Taktile's deep
00:16:44.079 --> 00:16:46.160
experience in decision-m remember this
00:16:46.160 --> 00:16:48.079
is a this company has been around for a
00:16:48.079 --> 00:16:49.920
while and we have a lot of C customers
00:16:49.920 --> 00:16:52.480
in production. I think that gives us a
00:16:52.480 -->
00:16:55.680
real uh compelling advantage over sort
00:16:55.680 --> 00:16:57.279
of newcomers. In particular, when I
00:16:57.279 --> 00:16:58.560
think about newcomers, I usually think
00:16:58.560 --> 00:17:01.279
about the AI startups who I think
00:17:01.279 --> 00:17:04.400
underestimate the complexity of the of
00:17:04.400 --> 00:17:06.559
business processes or the complex
00:17:06.559 --> 00:17:08.880
business needs of financial customers
00:17:08.880 --> 00:17:10.240
even though they're coming with great
00:17:10.240 --> 00:17:12.240
models like we have those models too.
00:17:12.240 --> 00:17:14.640
Um, but we also have years of context in
00:17:14.640 --> 00:17:16.640
the industry. I think that gives us a uh
00:17:16.640 --> 00:17:17.839
compelling advantage there.
00:17:17.839 --> 00:17:20.400
James, I really like the idea about how
00:17:20.400 --> 00:17:24.319
to prevent uh the bias. Um I believe if
00:17:24.319 --> 00:17:26.000
I'm sure at one point your customers
00:17:26.000 --> 00:17:28.480
will come to you and help to implement
00:17:28.480 --> 00:17:31.600
that and uh we really wish you good luck
00:17:31.600 --> 00:17:34.400
with that and good luck in your career
00:17:34.400 --> 00:17:36.720
at Taktile. Hopefully in a couple of
00:17:36.720 --> 00:17:38.400
years perhaps we will have you again on
00:17:38.400 --> 00:17:40.960
the show. Uh but today we really enjoy
00:17:40.960 --> 00:17:42.880
we really uh enjoyed the insights that
00:17:42.880 --> 00:17:44.240
you shared. Thank you for coming on the
00:17:44.240 --> 00:17:45.120
show.
00:17:45.120 --> 00:17:47.039
Great to be here. Cheers guys.
00:17:47.039 --> 00:17:47.919
Thank you James.
00:17:47.919 --> 00:17:49.679
All right everyone today we have Sadra
00:17:49.679 --> 00:17:51.919
Hosseini on the ground with us. Sadra is
00:17:51.919 --> 00:17:54.000
the co-founder and CEO of Ryft, a
00:17:54.000 --> 00:17:55.679
Manchester based payment company that
00:17:55.679 --> 00:17:58.160
helps marketplace and platforms take
00:17:58.160 --> 00:18:00.799
payments and split them between sellers.
00:18:00.799 --> 00:18:03.120
Last month, Lyft raised 20 million
00:18:03.120 --> 00:18:05.679
pounds. Sadra, welcome on the show and
00:18:05.679 --> 00:18:07.200
it's great to see you again after
00:18:07.200 --> 00:18:08.720
Fintech meet up Europe.
00:18:08.720 --> 00:18:10.160
Thank you very much for having me. I'm
00:18:10.160 --> 00:18:12.640
I'm excited to be here today.
00:18:12.640 --> 00:18:15.679
Sadra, uh, can you tell us um, a little
00:18:15.679 --> 00:18:17.600
bit about Ryft, what you guys are
00:18:17.600 --> 00:18:19.039
building and what problems you're
00:18:19.039 --> 00:18:19.919
solving?
00:18:19.919 --> 00:18:22.240
Of course. Of course. So, Ryft is the
00:18:22.240 --> 00:18:24.320
payments infrastructure for multi-party
00:18:24.320 --> 00:18:27.600
commerce. What that means is um any any
00:18:27.600 --> 00:18:29.440
business that needs split payments. Uh
00:18:29.440 --> 00:18:31.440
so, that's marketplaces as you said,
00:18:31.440 --> 00:18:35.039
digital platforms or franchises where
00:18:35.039 --> 00:18:36.960
I'll give you an example. Uh let's say
00:18:36.960 --> 00:18:39.919
Uber Eats, you payund100 for your
00:18:39.919 --> 00:18:41.919
dinner. That needs to be split three
00:18:41.919 --> 00:18:45.360
ways. So, £10 to driver, 20 to Uber,
00:18:45.360 --> 00:18:47.520
excuse me, £70 to a restaurant. That's
00:18:47.520 --> 00:18:49.440
where we sit. So, that's what I like to
00:18:49.440 --> 00:18:50.799
call commerce 2.0. You know, we're
00:18:50.799 --> 00:18:53.200
moving away from onetoone transactions
00:18:53.200 --> 00:18:55.039
where you go to Nike's website, you pay
00:18:55.039 --> 00:18:57.280
£100 for your shoes, and your payment
00:18:57.280 --> 00:18:59.120
processor would settle £100 into your
00:18:59.120 --> 00:19:02.559
account to now one to many and many to
00:19:02.559 --> 00:19:05.760
many. So that's that's where Ryft sits.
00:19:05.760 --> 00:19:09.039
Sadra, uh the story story goes that
00:19:09.039 --> 00:19:11.520
you've started Ryft because Butler, your
00:19:11.520 --> 00:19:13.600
pubing app, paid too much on Stripe
00:19:13.600 --> 00:19:17.520
fees. So uh what was expensive and when
00:19:17.520 --> 00:19:20.640
platforms move from Stripe to Ryft? Uh
00:19:20.640 --> 00:19:22.400
what is the main reason these days?
00:19:22.400 --> 00:19:24.960
Yes. Uh so Stripe is a very good kind of
00:19:24.960 --> 00:19:26.559
technical solution when you first start
00:19:26.559 --> 00:19:28.320
getting going. So if you're an early
00:19:28.320 --> 00:19:31.200
stage business, Stripe is is great. Uh
00:19:31.200 --> 00:19:33.039
and that's that's what we started. So we
00:19:33.039 --> 00:19:35.440
Bottler was a is a it was one app across
00:19:35.440 --> 00:19:36.720
all venues where you could order your
00:19:36.720 --> 00:19:39.120
food and drink within the venue. Uh we
00:19:39.120 --> 00:19:41.200
started that pre-COVID co hit. We scaled
00:19:41.200 --> 00:19:42.640
that to a million customers before it
00:19:42.640 --> 00:19:44.720
was acquired. And while we were building
00:19:44.720 --> 00:19:47.120
that business, we realized that once you
00:19:47.120 --> 00:19:49.520
go above 5 10 mil of volume, Stripe
00:19:49.520 --> 00:19:51.200
becomes a bottleneck for the platform
00:19:51.200 --> 00:19:54.400
itself. The reason for that is because
00:19:54.400 --> 00:19:56.240
Stripe has automated everything. They
00:19:56.240 --> 00:19:58.080
don't get to really understand these
00:19:58.080 --> 00:20:00.400
complex business models as as Butler was
00:20:00.400 --> 00:20:03.120
and as you see now kind of coming out
00:20:03.120 --> 00:20:06.640
with all these AI businesses. So because
00:20:06.640 --> 00:20:07.840
they don't get to understand the
00:20:07.840 --> 00:20:09.520
business, the underwriting and
00:20:09.520 --> 00:20:12.080
compliance will suddenly switch
off sub
00:20:12.080 --> 00:20:14.559
accounts. They'll pause payouts. They'll
00:20:14.559 --> 00:20:17.120
freeze accounts. So it becomes an
00:20:17.120 --> 00:20:19.120
operational nightmare for the platform
00:20:19.120 --> 00:20:21.919
itself. And then as you said there,
00:20:21.919 --> 00:20:24.880
Stripe is notoriously very expensive. Uh
00:20:24.880 --> 00:20:26.960
the reason there is they've got a lot of
00:20:26.960 --> 00:20:28.400
good merchants that they're monetizing
00:20:28.400 --> 00:20:29.679
but they also have a lot of bad
00:20:29.679 --> 00:20:31.120
merchants where they have to cover the
00:20:31.120 --> 00:20:32.320
chargebacks, they have to cover the
00:20:32.320 --> 00:20:35.039
fraud, uh the default rate and their
00:20:35.039 --> 00:20:37.120
support and operational cost is higher
00:20:37.120 --> 00:20:39.360
than if they went vertical by vertical.
00:20:39.360 --> 00:20:41.360
So that gets passed under the platform.
00:20:41.360 --> 00:20:43.280
The platform then can't monetize the
00:20:43.280 --> 00:20:45.520
transactions. That's where Ryft comes
00:20:45.520 --> 00:20:48.000
in. We we take care of all of that. We
00:20:48.000 --> 00:20:49.679
we really get to understand these
00:20:49.679 --> 00:20:52.400
business models and then we we allow the
00:20:52.400 --> 00:20:53.919
platform to monetize their own
00:20:53.919 --> 00:20:56.320
transactions in effect becoming their
00:20:56.320 --> 00:20:58.720
own stripe by using the Ryft Rails.
00:20:58.720 --> 00:21:01.440
As let's talk about the fundraising that
00:21:01.440 --> 00:21:04.480
you guys did um in one of our late shows
00:21:04.480 --> 00:21:07.679
we covered that UK fintech uh funding is
00:21:07.679 --> 00:21:09.520
at 10year low. I mean that's
00:21:09.520 --> 00:21:12.640
significant. So what did Graham House,
00:21:12.640 --> 00:21:14.400
one of your investors wanted to see
00:21:14.400 --> 00:21:17.120
before they invested in you actually?
00:21:17.120 --> 00:21:18.640
Yeah, a really good question. So,
00:21:18.640 --> 00:21:21.200
Gresham have led the round uh great
00:21:21.200 --> 00:21:23.200
investors. They've uh they kind of
00:21:23.200 --> 00:21:25.120
helped the business step into a full
00:21:25.120 --> 00:21:27.760
scaleup mode. Now, um Roit is the
00:21:27.760 --> 00:21:30.240
partner there who's uh invested in us.
00:21:30.240 --> 00:21:32.240
What they really cared about obviously
00:21:32.240 --> 00:21:35.440
there is the XC team like the CEO or the
00:21:35.440 --> 00:21:37.600
whole team around that how we how we
00:21:37.600 --> 00:21:39.840
operating, how well do we work together.
00:21:39.840 --> 00:21:42.320
One of the USPS of Ryft is the team
00:21:42.320 --> 00:21:44.640
itself that the whole team how we how we
00:21:44.640 --> 00:21:46.799
kind of move. We're very agile. were
00:21:46.799 --> 00:21:48.880
very adaptive. So they they were very
00:21:48.880 --> 00:21:50.720
happy with that. And off the back of
00:21:50.720 -->
00:21:52.640
that is obviously the traction as well.
00:21:52.640 --> 00:21:53.840
Like we we've been growing two and a
00:21:53.840 --> 00:21:55.840
half 3x year on year over the last five
00:21:55.840 --> 00:21:58.400
years. Um and the team has been
00:21:58.400 --> 00:22:00.960
outperforming uh any any of our closest
00:22:00.960 --> 00:22:03.200
competitors. So they they were very
00:22:03.200 --> 00:22:05.120
interested in Ryft. And then the final
00:22:05.120 --> 00:22:07.039
point to that is the payment
00:22:07.039 --> 00:22:10.400
sovereignty. So UK doesn't have its own
00:22:10.400 --> 00:22:13.679
sovereign payment uh platform. So you
00:22:13.679 --> 00:22:16.000
got Stripe which is US, you got um Adyen
00:22:16.000 --> 00:22:18.720
which is Netherlands. UK is missing its
00:22:18.720 --> 00:22:21.120
own version of these two businesses. So
00:22:21.120 --> 00:22:23.840
Ryft is the UK answer to Stripe and
00:22:23.840 --> 00:22:26.159
Aden. We're building the next gen of of
00:22:26.159 --> 00:22:28.400
UK payments growing globally.
00:22:28.400 --> 00:22:31.120
So 20 million um what's the plan with it
00:22:31.120 --> 00:22:32.559
now? What are they planning to spend it
00:22:32.559 --> 00:22:33.840
on first?
00:22:33.840 --> 00:22:35.280
Yeah, [laughter]
00:22:35.280 --> 00:22:37.280
I wish I could say Ferraris and Lambos,
00:22:37.280 --> 00:22:39.840
but yeah, it's going towards scaling the
00:22:39.840 --> 00:22:42.880
business. Uh the reason we raised was uh
00:22:42.880 --> 00:22:44.080
as I said we're we're growing
00:22:44.080 --> 00:22:45.760
internationally. So we're growing into
00:22:45.760 --> 00:22:48.799
the EU, growing into the US. Uh two
00:22:48.799 --> 00:22:51.360
reasons for that. So our customer base
00:22:51.360 --> 00:22:52.720
are growing. So they're growing
00:22:52.720 --> 00:22:54.320
internationally. So we we're growing as
00:22:54.320 --> 00:22:55.520
well to make sure that we can support
00:22:55.520 --> 00:22:58.880
them. But also Europe is where it's
00:22:58.880 --> 00:23:02.320
getting super exciting. Europe is um
00:23:02.320 --> 00:23:03.919
underpenetrated with these platforms,
00:23:03.919 --> 00:23:06.000
but it's growing 20% yearonear over the
00:23:06.000 --> 00:23:09.120
next five six years. uh and Europe is
00:23:09.120 --> 00:23:10.880
also very fractured. So every country
00:23:10.880 --> 00:23:12.240
has its own payment method. Every
00:23:12.240 --> 00:23:14.000
country has its own own language, own
00:23:14.000 --> 00:23:16.240
culture, but these these European
00:23:16.240 --> 00:23:18.400
businesses are growing into the whole
00:23:18.400 --> 00:23:20.559
Europe and then into the US as well. So
00:23:20.559 --> 00:23:22.960
we've raised this money to build that
00:23:22.960 --> 00:23:24.720
perfect solution for these European
00:23:24.720 --> 00:23:27.039
merchants who are then globing globally
00:23:27.039 --> 00:23:28.799
themselves.
00:23:28.799 --> 00:23:32.480
Sadra, look um in
April 2025, you told
00:23:32.480 --> 00:23:34.799
Business Insider that the Ryft uh has
00:23:34.799 --> 00:23:38.400
already broken even um and your but but
00:23:38.400 --> 00:23:41.919
your 2025 accounts at company's house
00:23:41.919 --> 00:23:46.080
show losses uh loses uh grew by 1.8
00:23:46.080 --> 00:23:48.240
million pounds. So are you guys
00:23:48.240 --> 00:23:49.760
profitable at the moment?
00:23:49.760 --> 00:23:52.320
No. So we uh we basically hit break even
00:23:52.320 --> 00:23:54.799
and then we raised our series A um and
00:23:54.799 --> 00:23:56.720
then since then we've been growing. The
00:23:56.720 --> 00:23:59.120
reason we raised series B was to
00:23:59.120 --> 00:24:01.600
obviously keep growing. Um, so we're
00:24:01.600 --> 00:24:03.520
still burning cash, but with the series
00:24:03.520 --> 00:24:06.400
B, we're going to hit profitability. Um,
00:24:06.400 --> 00:24:09.039
and if we go to raise again, it would be
00:24:09.039 --> 00:24:11.279
for M&A. There's a lot of opportunity in
00:24:11.279 --> 00:24:12.640
the market. There's a lot of
00:24:12.640 --> 00:24:14.159
consolidation happening as you've seen
00:24:14.159 --> 00:24:16.640
with World Pay and Global Payments. Um,
00:24:16.640 --> 00:24:18.320
I think a couple of other big providers
00:24:18.320 --> 00:24:20.640
are looking to emerge as well. So
00:24:20.640 --> 00:24:22.159
there's a there's an opportunity for
00:24:22.159 --> 00:24:24.720
Ryft to keep acquiring these businesses
00:24:24.720 --> 00:24:26.559
and kind of grow the customer base much
00:24:26.559 --> 00:24:29.520
more rapidly than organic growth.
00:24:29.520 --> 00:24:31.360
You you you already mentioned about
00:24:31.360 --> 00:24:32.880
international expansion. I think in the
00:24:32.880 --> 00:24:35.679
same business insider piece uh you said
00:24:35.679 --> 00:24:38.880
that Ryft would launch in US in 2025.
00:24:38.880 --> 00:24:40.559
When will US customers be able to use
00:24:40.559 --> 00:24:41.360
Ryft?
00:24:41.360 --> 00:24:43.840
Yeah, so we have uh US customers live
00:24:43.840 --> 00:24:46.480
already. We're basically building out
00:24:46.480 --> 00:24:48.559
more of the proposition. Uh the solution
00:24:48.559 --> 00:24:51.279
that we have right now is mostly online.
00:24:51.279 --> 00:24:54.400
Uh in in UK and Europe we've launched a
00:24:54.400 --> 00:24:56.559
card presence so omni channel so you can
00:24:56.559 --> 00:24:58.880
take payments online offline wherever
00:24:58.880 --> 00:25:00.640
the customer is. So we're looking to
00:25:00.640 --> 00:25:03.120
launch that in the US as well. Um and
00:25:03.120 --> 00:25:06.000
we're getting more embedded into the US
00:25:06.000 --> 00:25:07.760
ecosystem with the solution that we have
00:25:07.760 --> 00:25:10.400
there. So it's it's going to be more
00:25:10.400 --> 00:25:12.799
fledged out and and more featurerich
00:25:12.799 --> 00:25:14.960
rich product. But I think it's important
00:25:14.960 -->
00:25:18.159
to also note that we're not looking to
00:25:18.159 --> 00:25:20.799
capture a big market share in the US
00:25:20.799 --> 00:25:22.480
because even though US has a big
00:25:22.480 --> 00:25:25.279
penetration with platform 61%. It's also
00:25:25.279 --> 00:25:27.120
a very saturated market. You have the
00:25:27.120 --> 00:25:28.400
likes of Finex, you have the likes of
00:25:28.400 --> 00:25:30.240
Rainforest and obviously strip Stripe
00:25:30.240 --> 00:25:33.919
itself. Um so for us it's making sure
00:25:33.919 --> 00:25:36.480
that we as I said building that perfect
00:25:36.480 --> 00:25:38.320
solution for European merchants who then
00:25:38.320 --> 00:25:40.960
want to land in the US. So that's where
00:25:40.960 --> 00:25:42.880
we're going to we we are strongest at
00:25:42.880 --> 00:25:45.360
rather than just going purely US play.
00:25:45.360 --> 00:25:47.919
Sadra on our podcast one of the things
00:25:47.919 --> 00:25:50.159
that we usually do we cover latest tech
00:25:50.159 --> 00:25:52.400
news and we get the opinion of our
00:25:52.400 --> 00:25:54.480
guests uh on those news because we
00:25:54.480 --> 00:25:57.120
believe that they are um specialists in
00:25:57.120 --> 00:25:59.360
this. Um one of the latest news that
00:25:59.360 --> 00:26:01.520
caught our attention was Stripe uh
00:26:01.520 --> 00:26:04.000
acquiring Paraffin uh which lends money
00:26:04.000 --> 00:26:05.760
to small businesses through platforms
00:26:05.760 --> 00:26:08.480
like Door Dash. Since you are in a
00:26:08.480 --> 00:26:11.520
similar vertical, do you think uh Ryft
00:26:11.520 --> 00:26:13.679
will offer loans to sellers at one
00:26:13.679 --> 00:26:14.400
point?
00:26:14.400 --> 00:26:17.120
Yeah. So, we've uh we've been asked this
00:26:17.120 --> 00:26:19.600
multiple times over the years. The the
00:26:19.600 --> 00:26:20.720
reason that's a really interesting
00:26:20.720 --> 00:26:24.400
acquisition is Stripe as as we do, we
00:26:24.400 --> 00:26:27.039
have all the data on the on the sub
00:26:27.039 --> 00:26:28.640
account. So, the restaurants or the
00:26:28.640 --> 00:26:30.480
retailers, whoever it might be, we know
00:26:30.480 --> 00:26:32.400
how much volume they're processing. We
00:26:32.400 --> 00:26:35.360
know what's been bought and sold. So we
00:26:35.360 --> 00:26:38.080
can um allow them to have a pre-approved
00:26:38.080 --> 00:26:39.760
loan. They can click a button, money in
00:26:39.760 --> 00:26:41.279
their account, they can use that for
00:26:41.279 --> 00:26:42.960
cash flow. In the UK, it's called
00:26:42.960 --> 00:26:45.840
merchant cash advance. Um so we've
00:26:45.840 --> 00:26:47.760
already spoken to a few providers. We've
00:26:47.760 --> 00:26:50.240
got that kind of ready to go. It's just
00:26:50.240 --> 00:26:52.400
uh we have other priorities which is the
00:26:52.400 --> 00:26:54.080
international expansion before we bring
00:26:54.080 --> 00:26:56.320
a solution like that to market.
00:26:56.320 --> 00:26:57.840
Makes sense.
00:26:57.840 --> 00:27:00.720
And and other news is uh Mastercard who
00:27:00.720 --> 00:27:03.520
launched a service that payouts pays out
00:27:03.520 --> 00:27:05.120
uh both in normal money, fiat money and
00:27:05.120 --> 00:27:07.760
stable coins through one connector. Um
00:27:07.760 --> 00:27:09.679
we know that you guys have added 35
00:27:09.679 --> 00:27:11.840
currencies this month alone. Will you be
00:27:11.840 --> 00:27:15.720
offering stable coin payouts?
00:27:16.240 --> 00:27:18.400
Think me and Sam went through this uh on
00:27:18.400 --> 00:27:20.640
the panel as
00:27:20.640 --> 00:27:23.520
um there is a lot of buzz but we're not
00:27:23.520 --> 00:27:26.799
seeing requests. So obviously we're
00:27:26.799 --> 00:27:28.480
customer led. We make sure that whatever
00:27:28.480 --> 00:27:30.480
we're building is the perfect solution
00:27:30.480 --> 00:27:31.919
for our customers that we're working
00:27:31.919 --> 00:27:34.640
with. So we haven't really seen that
00:27:34.640 --> 00:27:37.039
much request from our customer base for
00:27:37.039 --> 00:27:39.360
stable coins. We're trying to figure out
00:27:39.360 --> 00:27:41.360
exactly where it fits because right now
00:27:41.360 --> 00:27:44.720
it's more um it might be beneficial for
00:27:44.720 --> 00:27:47.840
kind of crossborder uh money flows but
00:27:47.840 --> 00:27:49.520
then the problem there is the on-ramp
00:27:49.520 --> 00:27:51.600
and the offramp. You're still paying for
00:27:51.600 --> 00:27:52.880
those fees. It might be a little bit
00:27:52.880 --> 00:27:54.159
faster but you're still paying for those
00:27:54.159 --> 00:27:57.120
fees. So, we're we're holding we're
00:27:57.120 --> 00:27:59.440
holding fire. Uh we're going to see what
00:27:59.440 --> 00:28:00.799
happens with that market. I think what's
00:28:00.799 --> 00:28:03.279
more exciting is agentic payments, agent
00:28:03.279 --> 00:28:05.760
um agent eiccommerce. We're starting to
00:28:05.760 --> 00:28:07.760
see platforms kind of start requesting
00:28:07.760 --> 00:28:10.399
that, pushing for that, and that's where
00:28:10.399 --> 00:28:11.919
we're going to be focusing a lot of our
00:28:11.919 --> 00:28:14.240
energy over the next couple years.
00:28:14.240 --> 00:28:17.440
Right. Look um Sadra on our show uh when
00:28:17.440 --> 00:28:19.600
we speak to different executives from uh
00:28:19.600 --> 00:28:21.200
payments and fintech vertical they say
00:28:21.200 --> 00:28:23.279
one of the modes is to hold their
00:28:23.279 --> 00:28:26.559
license but to to hold their own license
00:28:26.559 --> 00:28:29.120
but flat pay in a Danish payment company
00:28:29.120 --> 00:28:31.120
chose to use adance license instead of
00:28:31.120 --> 00:28:33.840
holding its own you know and what what
00:28:33.840 --> 00:28:35.760
I'm trying to say that you I see that
00:28:35.760 --> 00:28:38.399
you are going uh after your own
license
00:28:38.399 --> 00:28:40.399
so do you want to have advantage on this
00:28:40.399 --> 00:28:42.799
and will continue applying for more and
00:28:42.799 --> 00:28:45.600
more licenses on different agents.
00:28:45.600 --> 00:28:49.039
Yeah. So, we definitely see that it's
00:28:49.039 --> 00:28:49.919
for [clears throat] us, for our
00:28:49.919 --> 00:28:51.679
business, it's fundamental for us to
00:28:51.679 --> 00:28:53.120
have our own license because if you
00:28:53.120 --> 00:28:54.880
don't have your own license, you're
00:28:54.880 --> 00:28:57.120
reliant on someone else like Aden, but
00:28:57.120 --> 00:28:59.200
also you're reliant on what their risk
00:28:59.200 --> 00:29:02.399
appetite is, how fast they can move. For
00:29:02.399 --> 00:29:04.880
example, when we on board a a platform,
00:29:04.880 --> 00:29:07.360
they might have 50,000 sub accounts. We
00:29:07.360 --> 00:29:09.120
can't rely on a partner to on board
00:29:09.120 --> 00:29:10.880
those uh because they'll they'll break
00:29:10.880 --> 00:29:12.480
down. We built all that all that
00:29:12.480 --> 00:29:14.720
in-house ourselves. So we need to have
00:29:14.720 --> 00:29:16.320
our own license, we have to have our own
00:29:16.320 --> 00:29:18.880
risk decision matrix to be able to on
00:29:18.880 --> 00:29:20.559
board these platforms and the sub
00:29:20.559 --> 00:29:22.960
accounts itself and then obviously if
00:29:22.960 --> 00:29:24.880
you have the license you build the tech
00:29:24.880 --> 00:29:26.880
as well. It gives you a bigger mode and
00:29:26.880 --> 00:29:28.720
it gives you a high margin as well. You
00:29:28.720 --> 00:29:30.159
don't have to rely on a partner to do
00:29:30.159 --> 00:29:32.480
everything. So for us it's fundamental
00:29:32.480 --> 00:29:34.960
that we have our own licenses.
00:29:34.960 --> 00:29:36.000
Makes sense.
00:29:36.000 --> 00:29:37.840
Well that was insightful Sadra. Thank
00:29:37.840 --> 00:29:39.120
you very much for coming.
00:29:39.120 --> 00:29:40.799
Thank you so much for having me. Really
00:29:40.799 --> 00:29:42.320
enjoyed the chat.
00:29:42.320 --> 00:29:44.320
Likewise, Sadra, we'll definitely stay
00:29:44.320 --> 00:29:46.320
in touch. May perhaps uh we'll have a
00:29:46.320 --> 00:29:49.039
chance to meet here in London. Uh if you
00:29:49.039 --> 00:29:51.279
are around uh there are many events are
00:29:51.279 --> 00:29:52.640
happening. Looking forward to it.
00:29:52.640 --> 00:29:54.799
Sounds good to me. Cheers, guys.
00:29:54.799 --> 00:29:55.360
Cheers.
00:29:55.360 --> 00:29:56.399
Bye-bye.
00:29:56.399 --> 00:29:59.200
All right, guys. Let's get back to um
00:29:59.200 --> 00:30:02.080
today's uh two breaking stories that we
00:30:02.080 --> 00:30:04.640
brought to you. First one is Barclays is
00:30:04.640 --> 00:30:07.840
cutting 5,000 jobs and it says AI is
00:30:07.840 --> 00:30:11.360
part of the reason. I thought AI um was
00:30:11.360 --> 00:30:13.600
uh bringing a lot of efficiency good
00:30:13.600 --> 00:30:15.200
things but we have to understand that
00:30:15.200 --> 00:30:17.600
with more efficiency there might be job
00:30:17.600 --> 00:30:19.600
cuts but it doesn't mean that every
00:30:19.600 --> 00:30:22.159
company is cutting the jobs only because
00:30:22.159 --> 00:30:25.200
of AI uh the may have some um role in
00:30:25.200 --> 00:30:27.520
this will go deeper into this and AI
00:30:27.520 --> 00:30:31.039
helped to find a security hole in PHP
00:30:31.039 --> 00:30:33.360
the code that runs the biggest part of
00:30:33.360 --> 00:30:35.919
the web and hackers start using it
00:30:35.919 --> 00:30:37.760
within the hours autobake so let's start
00:30:37.760 --> 00:30:40.080
with the first news sparkly is cutting
00:30:40.080 --> 00:30:43.520
about 5,000 jobs and around 5% of its
00:30:43.520 --> 00:30:45.760
staff worldwide. It announced the cuts
00:30:45.760 --> 00:30:48.559
on Thursday with its third quarter
00:30:48.559 --> 00:30:51.120
results. Uh about 1,000 jobs have
00:30:51.120 --> 00:30:53.679
already gone this year and uh the other
00:30:53.679 --> 00:30:57.120
4,000 will be gone by the end of 2026.
00:30:57.120 --> 00:30:59.600
Most are back office and support and the
00:30:59.600 --> 00:31:03.440
BBC says many cuts will fall in India.
00:31:03.440 --> 00:31:05.279
Ah, I believe this will hit the Indian
00:31:05.279 --> 00:31:07.279
economy really bad because those guys
00:31:07.279 --> 00:31:10.559
are uh India is hub for support jobs
00:31:10.559 --> 00:31:13.360
particularly and Barclay's results
00:31:13.360 --> 00:31:15.360
presentation talks about efficiency
00:31:15.360 --> 00:31:18.000
driven by AI and the banks expect to
00:31:18.000 --> 00:31:21.600
save more than 1.1 billion pounds in
00:31:21.600 --> 00:31:26.000
2027. Otabek is um this uh really AI or
00:31:26.000 --> 00:31:29.120
just cost cutting with AI label on it
00:31:29.120 --> 00:31:31.520
which is the question we ask so many
00:31:31.520 --> 00:31:33.600
times uh in our on our show.
00:31:33.600 --> 00:31:35.760
Well, I think it's partly AI. Yes. Uh
00:31:35.760 --> 00:31:37.360
many companies are seeing efficiency.
00:31:37.360 --> 00:31:41.360
The CEO of Barlay is uh Wata Krishnan on
00:31:41.360 --> 00:31:43.679
the call said AI is the icing on the
00:31:43.679 --> 00:31:46.159
cake but it's not the actual cake. The
00:31:46.159 --> 00:31:49.519
CFO and Cross said the cuts relate both
00:31:49.519 --> 00:31:51.200
to the simplification of the
00:31:51.200 --> 00:31:53.279
organization and to some of the impact
00:31:53.279 --> 00:31:56.399
that they were starting to see from AI.
00:31:56.399 --> 00:32:00.000
If you remember when we talked about the
00:32:00.000 --> 00:32:02.480
job cutting in Pipal and Coinbase uh
00:32:02.480 --> 00:32:05.519
back in May, we called it as you said uh
00:32:05.519 --> 00:32:08.480
AI whitewashing. But Barface has been
00:32:08.480 --> 00:32:11.360
going through the uh cost
optimization
00:32:11.360 --> 00:32:12.960
or cost cutting plan for the last three
00:32:12.960 --> 00:32:16.000
years. And um this is kind of a tale of
00:32:16.000 --> 00:32:17.600
it the last last year of the cost
00:32:17.600 --> 00:32:20.559
cutting program and it came out at the
00:32:20.559 --> 00:32:23.360
same time when they missed the profit
00:32:23.360 --> 00:32:26.080
target. The market was expecting them to
00:32:26.080 --> 00:32:29.519
make 2.4 billion uh pounds profit in
00:32:29.519 --> 00:32:33.919
this quarter. They did 2.3 billion. So
00:32:33.919 --> 00:32:36.480
again AI whitewashing or excuses for not
00:32:36.480 --> 00:32:38.080
missing the target that's that's a
00:32:38.080 --> 00:32:40.480
question that I think many analysts are
00:32:40.480 --> 00:32:44.559
are asking. However, Barclays do use AI
00:32:44.559 --> 00:32:47.440
in uh real business cases. Half of their
00:32:47.440 --> 00:32:50.000
developers are expected to move to
00:32:50.000 --> 00:32:51.919
Antropics quote code by the end of the
00:32:51.919 --> 00:32:55.279
year and uh they say they are already
00:32:55.279 --> 00:32:58.320
handling more than 120,000 client emails
00:32:58.320 --> 00:33:01.519
per day in their markets business. Who's
00:33:01.519 --> 00:33:04.000
actually losing the job? Do you see any
00:33:04.000 --> 00:33:06.799
push back? Uh are I mean employees who
00:33:06.799 --> 00:33:08.399
lost the job saying like you know this
00:33:08.399 --> 00:33:10.720
is AI washing um actually there's no
00:33:10.720 --> 00:33:12.240
efficiency. What's going on there?
00:33:12.240 --> 00:33:15.360
Well, we are talking about jobs in UK
00:33:15.360 --> 00:33:18.880
some and unions here are quite strong.
00:33:18.880 --> 00:33:21.120
We know that 60% of the cuts are coming
00:33:21.120 --> 00:33:23.760
to their support team and some of them
00:33:23.760 --> 00:33:27.279
are uh software developers. Unite which
00:33:27.279 --> 00:33:29.840
is the labor union in the UK said their
00:33:29.840 --> 00:33:32.080
general secretary Sharon Graham said the
00:33:32.080 --> 00:33:34.480
company's using AI as an excuse to disc
00:33:34.480 --> 00:33:37.200
to discard its loyal and long-suffering
00:33:37.200 --> 00:33:39.039
work workforce. And it's not just
00:33:39.039 --> 00:33:41.519
Barclays. Other UK banks are cutting
00:33:41.519 --> 00:33:44.000
jobs and citing AI for it as well.
00:33:44.000 --> 00:33:46.159
Standard Chartered announced that they
00:33:46.159 --> 00:33:51.440
are cutting 7,800 cuts jobs by 2030 and
00:33:51.440 --> 00:33:54.880
Lloyds are planning to cut 2 billion
00:33:54.880 --> 00:33:57.919
pounds by 2030 as well. Back in May
00:33:57.919 --> 00:34:01.039
again uh we discussed about uh JP Morgan
00:34:01.039 --> 00:34:04.720
CEO Diamond saying more AI people more
00:34:04.720 --> 00:34:07.600
AI will be replacing uh the bankers and
00:34:07.600 --> 00:34:10.720
we said if you remember if the junior
00:34:10.720 --> 00:34:13.520
roles
will be cut who will become the
00:34:13.520 --> 00:34:16.560
seniors in many years to come. Uh will
00:34:16.560 --> 00:34:19.520
hold the analyst from Quilty Chevad said
00:34:19.520 --> 00:34:22.000
the cats show how significantly AI and
00:34:22.000 --> 00:34:24.000
automation could reshape the banking
00:34:24.000 --> 00:34:26.320
industry over the next few years. I
00:34:26.320 --> 00:34:29.440
would really like to know again if these
00:34:29.440 --> 00:34:33.119
job cutings keep happening who will
00:34:33.119 --> 00:34:35.839
replace the junior roles and how they
00:34:35.839 --> 00:34:38.560
will plan to fill the senior roles in
00:34:38.560 --> 00:34:41.200
the future. I think you know what this
00:34:41.200 --> 00:34:44.079
was one of the questions uh which the
00:34:44.079 --> 00:34:48.240
audience asked um Jensen at Nvidia GTC.
00:34:48.240 --> 00:34:50.800
was almost the same question. Um and he
00:34:50.800 --> 00:34:54.079
said like yes uh we see there is some
00:34:54.079 --> 00:34:57.280
job cuts. Um there is a cycle I would
00:34:57.280 --> 00:35:00.640
say or job replacement but the thing is
00:35:00.640 --> 00:35:03.440
AI is creating more jobs too. We have to
00:35:03.440 --> 00:35:05.920
understand that and what needs to happen
00:35:05.920 --> 00:35:08.480
now. Uh this is I think simply the flow.
00:35:08.480 --> 00:35:11.760
Um it happened historically when some
00:35:11.760 --> 00:35:14.000
breakthrough happens some jobs will be
00:35:14.000 --> 00:35:16.079
lost but some more will be created which
00:35:16.079 --> 00:35:17.839
means the people who lost their job they
00:35:17.839 --> 00:35:21.040
will need to retrain themselves and uh
00:35:21.040 --> 00:35:23.920
learn more AI skills and then maybe go
00:35:23.920 --> 00:35:26.960
and find some other jobs that that that
00:35:26.960 --> 00:35:29.680
would fit their new skills uh that they
00:35:29.680 --> 00:35:31.839
um obtained. But again I would love to
00:35:31.839 --> 00:35:34.320
hear what our audience uh thinks about
00:35:34.320 --> 00:35:37.440
uh this topic uh if they are worried
00:35:37.440 --> 00:35:39.920
that AI will come after their job and
00:35:39.920 --> 00:35:43.119
they soon may lose um the job that they
00:35:43.119 --> 00:35:45.680
are doing and how they are actually
00:35:45.680 --> 00:35:48.720
preparing for machine economy for AI
00:35:48.720 --> 00:35:50.960
economy what exactly uh they are
00:35:50.960 --> 00:35:53.200
learning what skills they are obtaining
00:35:53.200 --> 00:35:54.880
please uh leave your thoughts in the
00:35:54.880 --> 00:35:56.640
comment section
00:35:56.640 --> 00:35:59.200
on to the next news uh well we discuss
00:35:59.200 --> 00:36:01.680
AI cutting shops at Barclays. Uh this
00:36:01.680 --> 00:36:04.079
week it is also found some security
00:36:04.079 --> 00:36:06.560
holes in big parts of the internet. On
00:36:06.560 --> 00:36:09.359
Wednesday, PHP released an emergency fix
00:36:09.359 --> 00:36:11.839
for two critical flaws called nicknamed
00:36:11.839 --> 00:36:15.599
PHP2Shell. PHP some as you know uh is a
00:36:15.599 --> 00:36:18.000
programming language and majority of the
00:36:18.000 --> 00:36:20.240
website on internet run on it. Uh
00:36:20.240 --> 00:36:23.200
WordPress and many other online shops.
00:36:23.200 --> 00:36:27.599
W3 tech says that about 70% 70% of the
00:36:27.599 --> 00:36:30.240
sites where it can detect the language
00:36:30.240 --> 00:36:34.079
uh run on PHP. These flaws are kind of
00:36:34.079 --> 00:36:37.359
nicknamed PHP2Shell and they let an
00:36:37.359 --> 00:36:39.599
attacker to take control of web server
00:36:39.599 --> 00:36:42.240
from anywhere. A security firm called
00:36:42.240 --> 00:36:45.359
Calif uh working on OpenAI program and
00:36:45.359 --> 00:36:47.599
the cloud security company V found them
00:36:47.599 --> 00:36:50.000
uh with the help of AI models. the
00:36:50.000 --> 00:36:52.240
details were leaked and before anyone
00:36:52.240 --> 00:36:54.560
could fix them the obviously uh
00:36:54.560 --> 00:36:57.680
attackers uh started uh to take over the
00:36:57.680 --> 00:36:59.440
websites and attacks happening within
00:36:59.440 --> 00:37:01.680
the hours. The UK's National Cyber
00:37:01.680 --> 00:37:03.920
Security Center said organizations using
00:37:03.920 --> 00:37:07.599
any version of PHP are affected. So Sam,
00:37:07.599 --> 00:37:09.440
I'm not sure if you have experienced any
00:37:09.440 --> 00:37:11.200
issues using the websites but I have
00:37:11.200 --> 00:37:13.599
seen uh many government and private
00:37:13.599 --> 00:37:16.160
websites showing the warnings or not
00:37:16.160 --> 00:37:19.520
working uh this week. So it is kind of
00:37:19.520 --> 00:37:22.400
uh concerning. So I'm not quite sure
00:37:22.400 --> 00:37:24.800
what to make of it. Uh AI finding the
00:37:24.800 --> 00:37:27.599
bugs and showing the deficiencies from
00:37:27.599 --> 00:37:29.760
one side it seems like a good thing.
00:37:29.760 --> 00:37:33.119
People are patching up their uh leaky uh
00:37:33.119 --> 00:37:35.200
kind of codes. But on the other side
00:37:35.200 --> 00:37:37.040
obviously all these hacks and takeover.
00:37:37.040 --> 00:37:38.880
So I'm not sure if it's a good news or
00:37:38.880 --> 00:37:41.599
bad news that AI is doing all this. I
00:37:41.599 --> 00:37:43.520
mean this is I think the still open
00:37:43.520 --> 00:37:46.800
question as you said um AI trying to
00:37:46.800 --> 00:37:48.640
help um let's say cyber security
00:37:48.640 --> 00:37:50.480
professionals to find the holes but on
00:37:50.480 --> 00:37:52.720
the other hand the same hackers are
00:37:52.720 --> 00:37:54.960
using those holes again to go and break
00:37:54.960 --> 00:37:57.119
into websites I didn't come across any
00:37:57.119 --> 00:37:59.920
uh warnings just yet but it was all over
00:37:59.920 --> 00:38:02.400
on my news feed that saying like a lot
00:38:02.400 --> 00:38:04.640
of
sites were taken down and the
00:38:04.640 --> 00:38:06.720
companies are working hard on patching
00:38:06.720 --> 00:38:10.079
all of those bugs and issues. So the bug
00:38:10.079 --> 00:38:12.160
actually autobex had in PHP for more
00:38:12.160 --> 00:38:13.920
than 10 years. It's not that something
00:38:13.920 --> 00:38:15.680
that happened yesterday. It was there
00:38:15.680 --> 00:38:18.400
for 10 years and AI helped actually to
00:38:18.400 --> 00:38:20.560
find and I think bring it to the
00:38:20.560 --> 00:38:22.480
attention. It usually happens. I think
00:38:22.480 --> 00:38:25.040
one of the best things about AI is that
00:38:25.040 --> 00:38:27.200
since uh sometimes the things that we
00:38:27.200 --> 00:38:29.040
are doing are too large and we are not
00:38:29.040 --> 00:38:31.280
able to pay attention to every and each
00:38:31.280 --> 00:38:33.200
detail of the things and AI could bring
00:38:33.200 --> 00:38:35.760
that to our attention and in this case I
00:38:35.760 --> 00:38:38.320
think this is what exactly happens and
00:38:38.320 --> 00:38:41.200
the thing is um attackers can use um the
00:38:41.200 --> 00:38:43.440
same models again as we said to hack
00:38:43.440 --> 00:38:46.480
into the websites we u wrote and I'm
00:38:46.480 --> 00:38:49.119
quoting frontier AI model substantially
00:38:49.119 --> 00:38:51.280
reduce the barrier turning a
00:38:51.280 --> 00:38:53.760
long-standing flow into an exploit. An
00:38:53.760 --> 00:38:56.160
exploit that is working at code that
00:38:56.160 --> 00:38:59.440
attacks the bug. TJ sireers of the
00:38:59.440 --> 00:39:01.680
center of internet security told fortune
00:39:01.680 --> 00:39:04.320
PHP2Shell shows how AI can help
00:39:04.320 --> 00:39:07.440
uncover um buried flows and turn complex
00:39:07.440 --> 00:39:09.920
exploit chains into practical attacks.
00:39:09.920 --> 00:39:12.640
What worries me the most is that Calif
00:39:12.640 --> 00:39:15.119
saying it didn't need special access. um
00:39:15.119 --> 00:39:18.160
it um its words uh were no special
00:39:18.160 --> 00:39:21.119
harness or access uh to models that were
00:39:21.119 --> 00:39:23.200
uh that weren't generally available to
00:39:23.200 --> 00:39:25.359
anyone were used. So basically they use
00:39:25.359 --> 00:39:28.480
the same available tools to everyone I
00:39:28.480 --> 00:39:30.800
think uh from their words. So uh these
00:39:30.800 --> 00:39:32.960
are the tools uh that anyone can use on
00:39:32.960 --> 00:39:35.520
September 7 autobec we covered that open
00:39:35.520 --> 00:39:39.359
AI chip 6 Astra actually reaching its
00:39:39.359 --> 00:39:42.000
critical cyber level and I I said I
00:39:42.000 --> 00:39:45.359
remember that that banks share the same
00:39:45.359 --> 00:39:47.839
open uh source code and I mean it's
00:39:47.839 --> 00:39:49.760
obvious you know there are couple of
00:39:49.760 --> 00:39:52.320
major um players uh banking software
00:39:52.320 --> 00:39:54.960
players uh that are available out there
00:39:54.960 --> 00:39:58.880
and um if one goes down one of those
00:39:58.880 --> 00:40:01.920
software providers It means number of
00:40:01.920 --> 00:40:03.520
banks will be affected. It's not that
00:40:03.520 --> 00:40:06.000
the one bank or fintech provider will be
00:40:06.000 --> 00:40:08.640
affected. We should expose major like
00:40:08.640 --> 00:40:11.440
who who is exposed uh who are those uh
00:40:11.440 --> 00:40:14.400
under the risk and what does it mean to
00:40:14.400 --> 00:40:16.079
uh for the banks for the payments or
00:40:16.079 --> 00:40:17.760
other players in our industry that we
00:40:17.760 --> 00:40:18.880
cover.
00:40:18.880 --> 00:40:20.640
Let's start with the major names. Uh
00:40:20.640 --> 00:40:22.960
some of them are WooCommerce uh that
00:40:22.960 --> 00:40:26.320
runs on WordPress, Magento which uh now
00:40:26.320 --> 00:40:29.280
Adobe Commerce. uh those guys are all
00:40:29.280 --> 00:40:31.680
built on PHP. These are already one of
00:40:31.680 --> 00:40:34.000
the biggest um platforms in the world
00:40:34.000 --> 00:40:36.320
and people actually built on top of
00:40:36.320 --> 00:40:40.320
these platforms uh their shops uh and
00:40:40.320 --> 00:40:41.920
they of course connect the payment
00:40:41.920 --> 00:40:44.000
systems to those shops and then
00:40:44.000 --> 00:40:46.560
obviously this can and those uh shops
00:40:46.560 --> 00:40:49.280
can get easily exposed and they attacks
00:40:49.280 --> 00:40:52.160
came fast autoic after the actually the
00:40:52.160 --> 00:40:54.560
incident started. Cloudflare's CEO
00:40:54.560 --> 00:40:57.040
Matthew Prince told Fortune there were
00:40:57.040 --> 00:40:59.839
tens of thousands of attacks attempts in
00:40:59.839 --> 00:41:02.720
the first 45 minutes in the first 45
00:41:02.720 --> 00:41:05.440
minutes and millions by that evening. I
00:41:05.440 --> 00:41:07.359
mean that the numbers are staggering and
00:41:07.359 --> 00:41:10.720
it's huge and help security reports that
00:41:10.720 --> 00:41:13.680
Amazon sensor saw one attempt 4 days
00:41:13.680 --> 00:41:16.079
before the fix the systems that could be
00:41:16.079 --> 00:41:19.680
at risk. You see it happened even before
00:41:19.680 --> 00:41:22.240
the news were released that that there
00:41:22.240 --> 00:41:24.800
is a hole. Someone already notes that
00:41:24.800 --> 00:41:27.359
and started there and not in a good way.
00:41:27.359 --> 00:41:29.040
Obviously it seems like they start
00:41:29.040 --> 00:41:31.599
attacking which means I mean uh hackers
00:41:31.599 --> 00:41:35.599
are um ahead of white blackhead hackers
00:41:35.599 --> 00:41:37.359
I would say are ahead of white hat
00:41:37.359 --> 00:41:41.280
hackers if you can say so and if AI can
00:41:41.280 --> 00:41:43.680
find the bugs uh that's been there for
00:41:43.680 --> 00:41:45.839
10 years and I want to know how many
00:41:45.839 --> 00:41:48.480
more out there it's very interesting and
00:41:48.480 --> 00:41:51.280
important question and as AI keeps
00:41:51.280 --> 00:41:53.920
developing we'll definitely find out
00:41:53.920 --> 00:41:56.480
what's going to happen next of today
00:41:56.480 --> 00:41:59.200
indeed I It will get worse until it gets
00:41:59.200 --> 00:42:02.560
better. Uh AI is improving efficiency
00:42:02.560 --> 00:42:06.000
throughout uh in jobs in coding as well.
00:42:06.000 --> 00:42:09.119
But obviously until we reach that
00:42:09.119 --> 00:42:11.839
efficiency, we are vulnerable and uh
00:42:11.839 --> 00:42:16.960
many ill people will uh try to use that
00:42:16.960 --> 00:42:19.520
vulnerability. Uh again the question to
00:42:19.520 --> 00:42:22.000
our viewers uh does AI make the internet
00:42:22.000 --> 00:42:24.319
safer or more dangerous? Uh and if you
00:42:24.319 --> 00:42:25.920
run a website, have you already patched
00:42:25.920 --> 00:42:28.480
it? write it in the comments.
00:42:28.480 --> 00:42:30.319
Yeah, definitely. We would love to learn
00:42:30.319 --> 00:42:32.720
more what you think where we are going
00:42:32.720 --> 00:42:35.920
in this world of AI. But uh from the
00:42:35.920 --> 00:42:38.560
talks at NVITA GTC, the world seems to
00:42:38.560 --> 00:42:40.480
be bright and we are going towards
00:42:40.480 --> 00:42:43.280
bright the future. But these news show
00:42:43.280 --> 00:42:46.880
that there is some dark sides of uh AI
00:42:46.880 --> 00:42:48.960
and how it could be used. Leave your
00:42:48.960 --> 00:42:50.960
thoughts in the comments and that was on
00:42:50.960 --> 00:42:53.040
the ground. Stay tuned for the next
00:42:53.040 --> 00:42:56.800
episode next Monday.