Day 3 closed out Fin Labs New York on a high note. Paul Adams, CPO at Fin, opened the day with an executive briefing that set the context for everything that followed. Then Dee Kapila, Rati Zvirawa, and Angel Horowitz from DaySmart led a fireside on where AI agents actually stand today, and what it takes for teams still on the sidelines to make their move. Next, Rigby Crawford, Santiago Luque, and Eric Broulette from Bloomerang walked through what great Fin deployment looks like in practice, with real examples from real teams. Then Brian Donohue closed the event with Prithvi Rajasekaran from Anthropic, telling the story of how doubling engineering productivity with AI unlocked something bigger: a full product rebuild and a new baseline for what a modern product team can ship. Three days in midtown. Hundreds of leaders and practitioners who showed up ready to build. Thank you to everyone who joined us and made Fin Labs New York what it was. We're just getting started.

Most voice AI products are slow because they're stitched together: speech to text, a general model, text back to speech. Fin Voice 2 is different. Purpose-built for the demands of customer service, with a separate real-time speech layer and a dedicated answer layer. Built on Apex Flash, our fastest model yet – Fin Voice 2 is faster, more natural, and ready for production. Take a look and try Fin Voice 2 for yourself ↓

Two months ago, we announced Apex 1.0, the world's first proprietary CX model that beat all foundation models on resolution rate, latency, and cost for customer experience use cases. No other company, whether new startup, or incumbent has since released anything comparable. Today, we release a further brand new model called Apex Flash. A smaller model with high performance, but specifically designed to be even faster. There are instances where you're happy for a model to take its time, but in many cases, time will always be of the essence. That's where our new model comes in. And tomorrow, we're announcing our first major new product that runs on Apex Flash…

We’re off and running at Fin Labs New York. Three days of practical, hands-on sessions on scaling AI in customer experience: automation, performance, team design, and building trust in AI Agents. Join us and you'll leave with a clear plan for what to test, implement, or scale next. This afternoon kicks off with our Founder Launch Studio before this evening’s meetup with Clay, exploring how to scale CX in the AI era. We’re just getting started, see the full 3-day in-person event schedule at the link in the replies (and register if you’re in NYC this week!)

@attio replaced their contact form with a conversation, and it changed how they sell. Instead of routing new visitors to a static form, Attio used Fin for Sales and built a real-time conversational entry point that qualifies prospects, answers complex product questions, and routes leads to the right next step. 24/7, without adding headcount. The results after 3 months: → 9x increase in Messenger engagement from new leads → 50 sales-qualified leads generated → 30 startup program qualifications → One converted customer came in at 6x their average contract value Matt Duffy, Head of New Business at Attio, saw where it was headed: "This is going to be the buying experience. More and more people are going to be doing this." Fin isn't just a support agent. It's an AI Customer Agent – handling support, qualifying leads, and driving revenue across the entire customer journey. Read the full story here: fin.ai/customers/attio

The sales funnel is fundamentally different from service. You're not resolving a problem. You're engaging with a lead, learning about them, and guiding them to the next stage of a deal. That required us to rethink the job Fin was doing from the ground up, and build Fin for Sales from scratch. Watch Fedor Parfenov, Bethany Clark, and Ratidzo Zvirawa talk through the architecture and product decisions behind Fin's new sales role, and learn more about Fin for Sales in the replies.

At our Operator launch in San Francisco, we made something clear: the Fin platform isn't built just for AI agents; it's built for the humans on your team too. → Unified Insights across agents and humans. → Unified QA across agents and humans (There's no other platform where you can do this.) One platform to run your entire customer operation, exactly as it is today. Learn more about Operator at the link in the replies.

"We made a conscious decision to become Fin's best reference customer by redesigning our support model entirely around AI." That's @decivory, our VP of Customer Support. And we did exactly that. Before any other business deployed Fin, our own team did. We went all in: new roles, new workflows, new standards. The results? Support didn't shrink. It got better: - 83% of support volume fully automated - 300% more demand absorbed as we've grown, without breaking - 2x increase in feature adoption and expansion revenue from proactive engagement - Every conversation that reaches a human is now genuinely complex, cross-functional, and technically demanding The question isn't whether AI can transform your support, it's whether you're ready to go all in. Read the full story linked below, and see what that looks like.

Most people can't describe exactly what they want. Fin for Ecommerce figures it out. It reads the intent behind a vague search, narrows your @Shopify catalog down to the right options, and helps customers convert with confidence. And for your customers, finding the right product stops being the hard part. Fin for Ecommerce is powered by Fin Apex 1.0, the best-performing model for customer service. Learn more about Fin for Ecommerce in the replies.

Most customer service teams are experimenting with AI. Very few are transforming because of it. The gap between those two things is larger than it looks; and right now, it's where the most consequential decisions in support are being made. Moving from a successful pilot to full production is where most teams struggle, so on May 27 we're hosting a session for the people doing exactly this work. Join Declan Ivory, Forrester guest speaker Max Ball, and AppFolio's Guneet Singh, XMP for a webinar that will cover: ➤ Why AI agents are changing the economics of support delivery, not just the speed ➤ What's actually shifted in AI reliability, scale, and quality over the last 18 months ➤ Why the jump from pilot to production is harder than most teams expect ➤ How leading teams sequence for ROI without trading away customer experience ➤ What moving from experiments to production at scale actually looks like We'll also walk through how AppFolio took their AI resolution rate from 17% to 73%, while holding a CX score of 93%. That kind of result doesn't happen by accident. Register at the link in the replies.

Earlier this month, the EMEA leg of our Customer Service Transformation tour came to a close in Amsterdam. One theme that surfaced throughout the evening: the teams making the most progress with AI aren't treating it like a tool. They've given it a name. Vera. Stella. Kiki. And to the people running support at Road, WebinarGeek, and ParkBee, it's a genuine member of the team with a role, a track record, and a personality. That framing changes how you build, how you measure, and how you get stakeholder buy-in. Thanks to our panelists: Marco, Bob, and Tim, to Caroline and Christopher for leading the discussions, and to everyone who joined us in Amsterdam! Stay tuned for information on the next stops on the Customer Service Transformation Tour.

Most engineering orgs are experimenting with AI. We bet the entire company on it, and hit our 2x productivity goal 3 months early. Join us on May 19 for a live session where Fin CTO @darraghcurran, Principal Engineers @brian_scanlan and Kesha Mykhailov, and special guest @clairevo break down how Fin’s ~500-person R&D org: • Shifted to agent-first engineering • Got 95% of PRs running through Claude Code • Cut defects by 55% • Shipped 2x more product changes at nearly half the cycle time You'll hear about the messy middle nobody talks about – uneven adoption, code quality dips, the human bottlenecks that mattered more than the technical ones, and what they'd do differently. Register at the link in the replies.

We recently launched the Spotlight Messenger, a brand new messenger experience built specifically for sales conversations. What makes it different: • Placed front and center on the page, because sales discovery benefits from focus. • No home screen, no tickets, no clutter. Ask a question, get an answer. • Smart suggestions that guide buyers who don't know what to ask yet. • A persistent "Book a Demo" CTA you can turn on or off. @Attio is already seeing the benefits from Spotlight Messenger – at our recent event in London, Will Jones shared that initial results show a ~90% increase in engagement. Learn more about Spotlight Messenger, and Fin for Sales at the link in the replies.

What can Operator do? It can run & optimize every feature across @fin_ai and the @intercom helpdesk. It finds trends & opportunities and suggests how to take advantage of them. It's your expert in the system.

Fin now handles the full ecommerce journey, from browsing to purchase to support, all in a single conversation. Fin answers questions as customers shop, recommends the right products, guides them to checkout, and continues supporting them after the purchase. One Agent, every stage. Connect your Shopify store in minutes with full knowledge of your catalog, pricing, and inventory. No complex setup required. Powered by Fin Apex 1.0 and a retrieval engine purpose-built for ecommerce, Fin delivers higher quality experiences across every interaction. Shopify merchants are already seeing higher conversion rates and increased average order value. Watch Brian and Robert (and Fin) go from discovery to cart to support, all in a single conversation. Learn more at the link in the replies.

Watch the full meetup conversation here: youtu.be/6sR9KJFncrQ

There’s a reality that’s starting to take shape: for some teams, AI is already handling the majority of customer conversations. At our recent Fin x @AnthropicAI meetup, we shared how this is already happening in practice. Fin now resolves over 80% of support queries end to end. The technology is here, but adoption is still catching up. That progress is unlocking something bigger. Fin is moving beyond support toward a broader vision, where one agent can deliver a consistent, high-quality experience across the entire customer lifecycle, from day zero to year ten. Watch more below to hear how close we are to that future, and what it takes to get there.

Learn more about Fin for Ecommerce here: fin.ai/ecommerce

Most AI Agents treat product catalogs like documents. That breaks when a shopper asks for anything with real constraints (like price, size, or availability) – because the system can return something that looks relevant but doesn’t actually satisfy what the customer asked for. Shopping queries have structure: price limits, sizes, stock, variants. So the Fin AI Group built a RAG system to handle both semantic intent and hard constraints in one system. This new system powers Fin for Ecommerce, a new role for Fin the Customer Agent How it works ↓ fin.ai/research/structured-a…