Intercom

When Nuuly first rolled out Fin, there was healthy skepticism. Natalie Hurst had a high-performing, deeply empathetic team, and wasn’t sure an AI Agent could match that level of care. But after giving Fin space to prove itself, the results have exceeded expectations. On a recent episode of The Ticket recoded live from Pioneer in NYC, Natalie shared what changed her mind, and how her team and customers have embraced AI as part of the support experience.

As the world slows down for the holidays, customer support doesn’t. While most are switching off, support teams stay switched on: fielding questions, solving problems, and making sure everything keeps moving behind the scenes. To every CS rep working through the festive season: 𝘁𝗵𝗮𝗻𝗸 𝘆𝗼𝘂. You’re the quiet heroes of the holiday season, and we see you. Your commitment means customers feel heard, helped, and supported whether it's December 25th or any other day of the year. Thank you for showing up and stepping in, even on the holidays.

Rolling out an AI Agent is only the beginning. Search Atlas, an AI-powered SEO platform, knew that long-term success required something more: continuous improvement. They treated Fin like a teammate, assigning a manager, shipping updates every three days, and revamping help content for AI-readability. The result? A jump from 30% to 70% resolution rate for incoming chats, all in under two months. “We started at around a 30% resolution rate, but through daily improvements to the knowledge base and the guidance we provide to our AI Agent, we’ve now reached about a 70% resolution rate for all incoming chats.” – Jonathan Kilton, Chief Revenue Officer at Search Atlas This playbook outlines how to manage, train, and evolve your AI Agent over time. If you want to go from 'live' to 'high-performing', start here.

“The one thing I’d really love attendees to walk away with is the realization that with AI technology and Fin in particular, you can really transform the customer journey.” The Blueprint for Scaling AI Support: live in Berlin event brought together 100+ CX and CS leaders to share real stories of scaling AI with Fin from launch to measurable impact. A huge thank you to our customer speakers who shared their insights and honest perspectives with the audience. Mark Oldenburg from Learnship, Paweł D. from Zalando, and Philip Janz from Ostrom shared how scaling AI with Fin helped their teams handle complexity, optimize workflows, and achieve tangible business results. And a special shoutout to Christine for a live demo of Fin Voice, giving attendees a firsthand look at how AI can transform support operations. The European leg of the Blueprint event series is complete! We're excited for Declan I. to take the tour stateside in the new year, continuing the conversation in New York and San Francisco ↓

Every customer service interaction in finance carries weight. Customers are making decisions about their money, their futures, and their long-term goals, so every response has to be accurate and timely. At IG Group, a global leader in online trading and investing, support is a core part of the value they offer. In this video, IG Group's Hannah Reid and Hayley Gibbs share how they're scaling support with Fin. The aim is to shift the routine, high-volume queries to AI, freeing up their specialists to focus on the moments that really matter. Since deploying Fin, they’ve launched AI support across chat, email, WhatsApp, and multiple languages. They’re seeing CX Scores in the 90s across channels, deflection rates of up to 70%, and more automation than they expected this early. For a highly regulated, highly emotive industry, Fin’s integrated front end, multi-brand configuration, and roadmap alignment were critical in helping IG Group deploy AI safely and confidently, without heavy development work. The outcome: faster resolution of routine queries, reduced operational load, and more time for human teams to deliver the kind of high-value service IG Group is known for. Watch how they made the shift ↓

Over the past 12 months, we shipped over 200 new products and features across Fin and Helpdesk, and announced Fin 3, designed to handle more complex queries, across more channels than ever before. The Fin Flywheel evolved to help teams train, test, deploy, and analyze with confidence, and along the way, Fin’s overall resolution rate continued to increase, closing the year at an average of 67% across all customers. Here’s a look back at the biggest product updates and customer highlights from 2025.

When it comes to AI Agents, there are many metrics you can track, but one you should focus on:   Automation rate. It tells you: • What share of your total volume AI is actually resolving. • How much work is left for humans to manage. • How much additional volume humans can absorb if demand increases. • How ambitious you can be with your headcount plan for next year. Swipe below to learn more about this key metric and how to use it in your 2026 planning. And for more advice on how to plan for an AI-first support model, check out the link in the comments.

Capacity planning has always been a high-stakes exercise in customer service. If you get it wrong, you’ll feel it quickly in backlogs and SLAs. But the dynamics have changed. As AI resolves more of your inbound volume, it also changes the work left for humans. It adds new work too, like reviewing the AI's behavior, improving systems, and feeding insights back into the business. None of that fits neatly into traditional models. So how do you set your customer service team up for success in 2026? Declan I., our own VP of Support, shares his thoughts on this in the final volume of our 2026 customer service planning series (link in the usual place). The image below summarizes his advice, the full article unpacks the reasoning behind it. If you’re navigating 2026 planning right now, this will help.

Scaling support in real estate is uniquely challenging: millions of residents, time-sensitive requests, and customers that rely on fast, accurate answers. For AppFolio, who supports 20,000+ property management companies, customer service is, "the heartbeat of why customers are actually buying the software itself." In this video, Guneet Singh, Vice President of Customer Experience & Care, shares how his team moved from a fully human support model to one where Fin, their AI Agent, now handles the majority of frontline conversations with remarkable quality and consistency. Today, Fin is involved in 60-70% of support conversations, and resolves 60-65% of them end-to-end. The results: faster answers, better quality, a CX Score of 93, and a support organization starting to evolve from agents to AI leaders and supervisors. This is a shift toward a future where AI amplifies human capability, enabling support organizations to deliver fast, high-quality service at scale, while elevating the roles of the people behind it. Watch how they made the shift ↓

AI is changing capacity planning more than most teams realize. The work your team does is changing, the pace is increasing, and previous assumptions about output, occupancy, and automation are likely out of date. In the final edition of our 2026 customer service planning series, Intercom’s VP of Customer Support, Declan I., shares how to build a capacity plan that actually works in an AI-first world. You’ll learn: • Why traditional metrics like productivity per person no longer hold up • Why automation rate, not resolution rate, should anchor your 2026 plan • How to protect time for improvement, not just inbox work • Why “surplus capacity” isn’t a problem, it’s your future advantage If AI is going to handle the majority of your volume, your plan needs to support that system and the people behind it. Read the fifth and final installment now ↓