The only helpdesk designed for the AI Agent era
Joined April 2025
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Watch the full product update video here:
youtube.com/watch?v=tTrABO4j…
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.
🤖 Made with AI
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.
Watch the full conversation about delivering high quality AI experiences here: youtube.com/watch?v=-53JZG9-…
“Trust has been a multi-year journey.”
At our recent Fin x @linear meetup, we explored what it actually takes to build trust in AI Agents, and why it starts with giving systems room to prove themselves, limiting their blast radius early on, and gradually expanding their role as customers see what they can reliably do without risk.
Watch more below to hear how teams are measuring and earning that trust in practice.
What does it actually take to move from deploying AI to using it in ways that change how a business operates?
That was the focus of our recent Fin x PostHog meetup in San Francisco. The conversation explored where companies are making real progress (and where things are still unsettled) – from the declining importance of traditional interfaces, to the realities of outcome-based pricing, and the challenge of driving true adoption inside organizations.
A big thank you to Tim Glaser, Co-founder of PostHog, and Junan Pang, VP of Customer Success and Solutions at Fin, for a candid and thought-provoking discussion – and to everyone who joined us and brought sharp questions to the room.
If you’d like to join a future Fin meetup, subscribe to our Luma calendar to see what’s next.
“You only pay for Fin when it does the job.”
At our recent Fin × @AnthropicAI meetup in Paris, this came up as a practical answer to a bigger question: how do you actually build trust in AI agents?
For Jordan Neill, it starts with aligning incentives. Fin is designed to resolve customer problems end to end, and you only pay when it does.
No usage-based ambiguity or paying for potential. Only outcomes.
It’s a simple idea, but it changes the relationship entirely. Trust is built into how the product works.
Watch the clip below.
To join a future Fin meetup in your city, subscribe to our Luma calendar.
Quality in AI isn’t just always a clean, single metric. It’s often something you feel when it works the way you expect, consistently.
That’s what we explored at our Fin x @Linear meetup in London.
@brian_donohue (Fin) and @matthijswolting (Linear) shared how teams are building for quality in practice, from combining AI scoring with human review, to creating visibility into what agents are doing and where they fall short. The throughline: trust is built by giving teams the tools to understand, test, and improve AI systems over time.
Watch the highlights below. And if you want to watch the full conversation, see the link in the comments.
If you’d like to join a future Fin meetup, subscribe to our Luma calendar to see what’s next.
Earlier this week in London, we partnered with @attio to explore how modern GTM teams are actually selling with AI, and where today’s approaches are still falling short.
The conversation, led by @rati_zv (Fin) and
@nicolasosharp (Attio), alongside @ciaran_nolan (Fin), focused on a growing mismatch: buyers are arriving faster, with more context and higher intent, but the systems they meet are still built for a slower, linear world.
That gap set the stage for something new. We introduced Fin for Sales. It works like the ultimate salesperson: engaging prospects at just the right moment, guiding product discovery, suggesting tailored options, and qualifying in real time so no lead gets left behind.
We also heard from Fin's @destraynor and Bethany Clark, and Attio's Will Jones, who shared how teams are starting to rethink the top of funnel, from static forms and handoffs to real-time, AI-led engagement.
One theme that stood out was the idea of “lossless context.” Not just within a single interaction, but carried from the very first website visit all the way through to long-term customer relationships. As AI takes on more of the execution, the opportunity is to design systems that remember, adapt, and build on every interaction, so nothing gets lost as prospects become customers.
From rethinking the role of the sales funnel to the emergence of new roles like GTM engineers, the discussion made one thing clear: this is more than simply adding AI to existing workflows, it’s redesigning them from the ground up.
Learn more about Fin for Sales at the link in the replies 👇
