Gradient Labs @GradientLabsAI

Last week in Amsterdam, we hosted a dinner for banking and finance leaders attending Money20/20 Europe. It was a great conversation with a few recurring themes: 🎯 C-suite caution can be overcome by meeting a clear bar. Fast ROI and measurable time and cost savings are critical proof points, so selecting the right problem to solve is arguably more important than fast implementation. 🔧 Teams aren’t looking to overhaul their existing processes. They want AI that works with current tech stacks, that can slot alongside how teams currently operate, and that non-specialists can manage day to day. ⚡ Every bank in the room could name something they'd struggled to scale for years. That's where AI delivers the clearest, fastest return. Thanks to everyone who came, and to the team at Sinne for a fantastic meal.

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We’re thrilled to announce that @current, a U.S.-based consumer fintech banking platform with over six million members, is partnering with Gradient Labs on their AI agent for customer operations. Current’s mission is to improve financial outcomes. They chose us as their partner because we've proven AI can improve those outcomes and lead to meaningfully stronger customer experiences. As the only AI agent purpose-built for financial services, Gradient Labs is helping Current deliver the kind of 24/7 support that is essential for building and maintaining customer trust.

POV: a week at @money2020 Europe in Amsterdam 🇳🇱 If you missed the key insights shared by our CTO @neal_lathia and Head of Marketing @emmalynefurlong this week, scroll back through our posts to read their takeaways. 📈 #Money2020EU

Every month, capital moves. The question is whether you're reading the signals or just the headlines. May 2026 had a Japanese entrepreneur choosing Ethiopia over Nigeria because the market was harder. Three ex-Monzo engineers automating bank compliance. And a Berlin lawyer who noticed that half of what law firms do has nothing to do with lawyering. Here are 10 raises that caught our attention at Pitchwise: - Dodai ($13M Series A): Yuma Sasaki chose Ethiopia deliberately. Ethiopia banned petrol vehicle imports. One policy explains the round. - Shiprazor ($2.65M Seed): Sahil Affriya, a former VC, built a logistics layer for African e-commerce: one integration, 20+ couriers, 1.5 million deliveries. @Norrsken22 leads. - @enzo_health ($20M Series A): Zach Newman's AI platform for home health grew revenue 40X in 24 months. 500,000 patients on the platform. N47 leads. - @GradientLabsAI ($26M Series A): Dimitri Masin, 🚀 Neal Lathia and Danai Antoniou met at Monzo. Revenue grew 900% in a year. @OctopusVentures and @commerzventures lead. - LawX (€7.5M Seed): Dr. Norman Koschmieder, Dr. Sara Brinkmann, and Torben Rabe. The operating system layer under the lawyers, not another AI for lawyers. @motive_partners leads. - Bayshore AI ($8M): German legaltech turning compliance rules into code. Y Combinator-backed. - @ComplyD0 (YC F25) ($1.3M Seed): Berlin compliance platform consolidates regulatory obligations. Backed by @ycombinator and Reaktor. - @rukahair ($4.5M Seed): Biotech beauty startup using scientifically formulated ingredients. Henkel Ventures co-leads. - @pollen (€3.2M Seed): Battery-swapping for electric mopeds in Portugal. The same thesis showed up in Addis Ababa this month. - BFREE (Undisclosed Growth Round): Julian Flosbach, Chukwudi Enyi, and Moses Nmor buy distressed loan portfolios and rehabilitate them ethically. @AfricInvest_Grp leads, and it is also Algebra Ventures' first investment in Nigeria. To every founder on this list, the round is just the receipt. The real work was convincing someone the bet was worth making. #Pitchwise #Startup #Fundraising

It's @emmalynefurlong here on the ground at @money2020 Europe, sharing a few reflections after three days of keynotes and conversations on the floor. Leaders across financial services are (rightly) adamant about maintaining their customers’ trust as they evaluate AI. I thought Amit Thawani, CIO of Insurance at @LBGplc, articulated this particularly well on the Engineering an AI native Bank Panel, where he said: When you’re working in high-stakes, emotional life moments like bereavements, you cannot afford to get the experience wrong. AI can reduce the operational burden, but the line between success and failure is in the customer experience. Empathy and CSAT matter just as much as efficiency. But the need for efficiency is not to be discounted, and was clearly top of mind at the show. Nearly everyone we spoke to at our booth had a specific, manual back-office process they’re struggling to automate. It seems the discourse is shifting from “How can I use AI?” to “I’ve outlined the biggest challenges in my business that are ripe for automation, now how do I use AI to solve those challenges safely, and without compromising customer experience?" It’s been validating to see the similarity in approach between how we run Gradient Labs, and the companies we serve: that any AI project must start with a clear business challenge, eliminate painful manual processes, and make the customer experience fundamentally better, all at the same time. #Money2020EU

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The real MVP of the conference. ☕️ #Money2020EU

@neal_lathia here, live from @money2020 Europe. Earlier this week we shared our increased $26M Series A, and then I landed straight on the conference floor in Amsterdam. Two days in, this is what I keep hearing: The build vs. buy question dominates every AI conversation in finance right now. My honest take is that it’s the wrong question to answer first, and possibly the wrong frame altogether. Every team I’ve spoken to that has gone down the internal build route has ended up with something narrower than planned, shipped later than expected, and still needing to wrap around things they had not anticipated. Whatever you build, you are building on top of something. Whatever you buy, you are building on top of that too. The conversations that go somewhere start differently: what are you actually solving for, and what does “good” look like for your business? That sounds obvious, but it is genuinely rare, and the teams making real progress are the ones who can answer that question precisely. Once you know what you’re looking for, you can test internal models against agents out there and see which performs best for your needs. Of course, I also stopped by the LHV Bank booth to say hi. Always good to see customers here in the wild. #Money2020EU

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Who remembers these robot dogs from 2000? We got this one off eBay for our booth at #Money2020EU and had a laugh at the description in the manual:

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Read the case study here: gradient-labs.ai/customers/pock…

Six months ago, Pockit came to us with two challenges: 1️⃣ Their legacy chatbot was deflecting tickets, but CSAT kept slipping. Customers didn't feel their problems were actually solved. 2️⃣ As Pockit scaled, support volume spiked in ways that were hard to plan for. Today, more than 7 in 10 inbound queries are resolved end-to-end by Gradient Labs’ AI agent, and customer satisfaction is 80%. The team did it without adding headcount. Michiel Smet, Head of Operations at Pockit, shared: "We truly think that if people have a problem and you solve it, that builds brand loyalty. That's why customer resolution is so important. With Gradient Labs, we have an AI agent that's actually resolving problems, boosting our CSAT rating, and absorbing growth.” Read Pockit’s story in the thread.

Our “good bot” team is live on the ground at @money2020 Europe. 🇳🇱 If you’re not on the conference floor with us, don’t worry: we’re about to bring it to you. For the next two days, our CTO and co-founder @neal_lathia and our Head of Marketing Emma Martin will take over the Gradient Labs account to bring you real insights and observations gained on the go at Money20/20. You can follow along here and on LinkedIn. And if you’re with us in Amsterdam, stop by our booth (5D58) to say hi and play with our retro robot dog. 🐕🤖 #Money2020EU

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💰@GradientLabsAI has expanded its Series A financing to $26 million, techfundingnews.com/ex-monzo-teams… It came from new investors @OctopusVentures and @commerzventures alongside follow-on backing from @Redpoint and Exceptional Capital. #ai #funding #uktech #london #innovation #vcfunding #investment #aiagents

When it comes to deploying AI, most of the conversation is around which model to use, what to automate, and whether the outputs are good enough. And while that’s important, there’s another piece to this puzzle: what does the product feel like to the people using it? We frequently run user research sessions with our customers, with the goal to better understand how operations teams feel about AI agents. How do they navigate them? What makes them feel simple to use? What builds confidence? We kept hearing two things: 1) Teams want an uncomplicated setup that leads to quick wins 2) Early results build confidence to go further There's an emerging group of AI-native operations leaders who live in these tools every day. They have high standards for what good looks like. In the same way we obsess over your customers' experience, we obsess over the experience of the people building with us.

"Demos are easy to create. The real difficulty starts when you try to build something that works reliably in practice." Our Chief Scientist @AntoniaDanai was interviewed for @FortuneGreece this week. The interview covers: 🦾 Why AI agents for financial services are so tricky to build 📈 Where AI outperforms humans (and vice versa) 💡 What our team has learned from implementation with real customers Read the article: eu1.hubs.ly/H0vFspt0

Read the guide here: gradient-labs.ai/voice-ai-testi…

Have you ever seen a messy AI voice demo? Chances are… probably not. Next opportunity you get, ask to see a demo where the caller mumbles, interrupts, discloses they've just lost their job, and then asks for financial advice before switching topics entirely. Our CEO Dimitri Masin calls that "a normal Tuesday afternoon in any financial services contact centre." In the real world, AI Voice needs to navigate all this and more. And in financial services the consequences of floundering in production are much worse than merely frustrating the end user. So what can you do? Rigorously test your AI agent before it ever calls a customer. We put together a guide with 40 core scenarios to test for, based on our live voice AI deployments. Check it out: eu1.hubs.ly/H0vyjkz0

ICYMI: we’re one of eight startups selected for @NatWestGroup's 2026 Fintech programme. 🏦 This year's theme is "How is AI shaping the future of customer experience?" Candidates needed to prove product-market fit, an active user base, and real revenue. They also needed to prove their product meaningfully changes how financial services companies handle the customer experience. Over the next 12 weeks, we’ll be partnering closely with NatWest’s Open Innovation team, exploring collaboration opportunities to advance customer experience with specialised AI agents across customer operations. Thrilled to be part of this programme. Stay tuned for what’s next.

In two weeks, our team will touch down in Amsterdam for @money2020 🇳🇱 You can chat with us at booth 5D58, where you'll catch our CTO Neal Lathia in his good bot hat. Ready to talk about… 🛠️ Getting an AI project from pilot to production 🏦 How leading banks and fintechs are automating disputes, KYC, and collections 📈 Real AI success stories from the biggest banks and fintechs in Europe We're also hosting a special, Michelin-starred dinner for anyone who wants to deep dive about these topics. 🌟 Leave us a comment if you want the details ⬇️

On 19th May, our CTO and co-Founder Neal Lathia will present on the panel: “Data You Can Defend: Building Decision-Grade Information” at the Banking Transformation Summit in London. 🎙️🇬🇧 Stop by the Gradient Labs booth to say hi to our team, and don’t miss the chance to ask Neal questions in the room.

Read more here: gradient-labs.ai/blog/introduci…

We’re working with more and more lenders across the UK, US, and Europe, and they all share the same challenge: lending is high-volume, time-sensitive, and compliance-heavy, which makes it difficult to scale. We’ve built an AI agent for lending that automates the borrower lifecycle, from application through to servicing and collections. Borrowers get fast, personalised support on every interaction, and lenders don’t have tickets sitting in queues. We’re already processing 100,000+ calls per month across our customer base, matching human recovery rates 1:1, and staying compliant at every step.