Intercom

The only helpdesk designed for the AI Agent era

[Intercom @intercom]

Watch the full product update video here:
https://t.co/KfqRkqtJII

[Intercom @intercom]

Tickets are where support work goes when it can’t be resolved in one reply, like a refund that needs finance or a bug that needs engineering.

We recently shipped nine improvements to tickets. These updates are designed to improve the teammate, customer and cross functional teams experiences from the moment a teammate creates a ticket, to the way teams track that work and customers follow its progress.

Three of the updates:
→ Fin autofills in the ticket title, description, and attributes from the conversation, so creating a ticket stops being a second round of data entry
→ A new lifecycle report shows how tickets move between teams, where they loop, and how long they sit with each one
→ You choose which status updates are worth an email, so customers stop tuning out the ones that matter

Live for everyone today. Watch the full product updates video at the link in the comments.

[Intercom @intercom]

@SteakFTH @AnthropicAI Hey Andrew – we've written about this in this article from our Blueprint Hub: https://t.co/HNQkW65I39

[Intercom @intercom]

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.

[Fin @fin_ai]

Shannon Magiera runs support at Kalshi with a team of eight. In 2024, they handled 30,000 tickets. In 2025, 115,000. This year, they're projecting over a million tickets.

When response times hit three, four, even five days, there simply wasn't time to help people the way they deserved.

The choice: hire 200 people or bring in AI.

They chose Fin. It handled the frontline questions. The team finally had time to sit with the harder tickets, build relationships, and earn trust.

As Shannon says, "It became more human."

AI didn't replace the human side of support, but it did give them room to actually do it.

If you're looking to hear how a team of eight navigated hypergrowth and scaled from a standing start to 75% resolution rate through constant iteration, watch the full session with Shannon from Fin Labs New York at the link in the replies

[Fin @fin_ai]

For many ecommerce brands, customer support is seen as a cost center, but for Ninja Transfers, it became a revenue driver. By integrating Fin with Shopify, the team extended it beyond support and into the buying journey itself.

Now, one in ten conversations with Fin ends in an order, with those orders averaging 20% above their typical order value, adding up to $73k in Fin-influenced revenue over just 14 days.

Here's how they got there.

Ninja Transfers sells custom direct-to-film transfers, where you can print any design on any product, material, or color. They're trusted by millions who create merch, crafts, gifts and more. This creates far more complexity than an online store offering off-the-shelf products.

Customers arrive with detailed questions, and if those questions go unanswered overnight, orders are lost.

Fin now surfaces the right products, helps customers build their cart, and walks them through application methods, all in the same conversation where it's answering support questions. Across their three brands, Fin handles tens of thousands of conversations a month, resolving around 80% of them end to end.

"Fin is like having a product expert available whenever a shopper needs help." – Matt Satell, Director of Ecommerce at Ninja Transfers.

Read the full story at the link in the replies.

[Fin @fin_ai]

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.

[Fin @fin_ai]

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 ↓

[Eoghan McCabe @eoghan]

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…

[Fin @fin_ai]

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!)

[Fin @fin_ai]

@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: https://t.co/wcb9JnKRTJ

[Fin @fin_ai]

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.

[Fin @fin_ai]

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.

[Fin @fin_ai]

"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.

[Fin @fin_ai]

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.

[Fin @fin_ai]

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.

[Fin @fin_ai]

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.

[Fin @fin_ai]

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.

[Fin @fin_ai]

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.

[Fin @fin_ai]

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.

[Eoghan McCabe @eoghan]

https://t.co/woWlW57HQf