Watch: Demos and Prototypes

At Intercom, we’re experimenting with new products and features every day, especially with AI. We’re exploring what the latest AI models can/can’t do.

We are now sharing some of the work in progress to give people a sense of what we’re up to, and maybe start a discussion with us. We’d love that!

April 2025

OTP for Fin Tasks

As AI Agents take on more complex and sensitive workflows, security can’t be an afterthought. It has to be built in from day one.

At Intercom, we’ve designed Fin with security as a first principle, enabling customers to configure multiple layers of protection, real-time verification flows, and safeguards that help maintain trust between agents and their customers.

In this demo, Fin supports a customer through a policy amendment, verifying their identity and then guiding them through the process step by step.

Take a look and let us know what you think.

AI Generated Fin Task Instructions

Last week, we shared a demo of Fin showing how we’re blending rules based (deterministic) and natural language based (generative) logic in Fin so that our customers can configure the exact customer journeys they need.

This is a very important thing to learn about and understand if you are using or building AI Agents.

But this whole area is new, it has never existed before the AI era, and so people need to learn how to do it. To help them, we’ve built a feature that uses AI to suggest instructions. Today we’ve a nice follow up demo showing how you can write structured Task instructions using natural language in Fin.

March 2025

Fin Tasks

The future of AI Agents is generative and deterministic workflows blended together, and Agents that complete full Tasks for customers.

Most businesses have complexity, and in exploring different ways Fin can work for our customers, it’s really clear that they need both generative and deterministic steps in single workflows. Here is a demo of our work in progress.

Fin in the Help Center

Knowledge bases are a critical line of defence for support teams but they can also become a bottleneck, leaving customers to sift through hundreds of articles to find what they need.

So we ran an experiment: using Fin to deliver faster, more direct answers inside the Help Center.

We’re still early in the test but already learning a lot about how AI can reshape self-serve support.

Fin Messenger experiments

Over the past month we have been very busy running a series of experiments on the design of Fin in our Messenger. We decided to challenge numerous design decisions that were meant to address problems from a different era.

Every new experiment lead to theories, every theory lead to new ideas and ideas with the best rationales made it to their respective A/B tests. The results were as interesting as the process itself. This demo shows the results, and how we think about our AI products and using data to refine our design decisions.

Fin Testing

As more customers use Fin, we’re learning how important it is to test how Fin answers different types of questions.

So we’ve been building new powerful testing tools. Here is a working beta of one of them.

What makes it so powerful is the ability to bulk test how Fin answers a set of questions. Plus, right below the answers, you’ll find details on the inputs used to generate each response, making it easy to troubleshoot and refine.

We’re already seeing how this is helping customers feel more confident in how Fin responds – and giving them the tools to make those responses even better.

Fin Guidance Assistant

We mortal humans are still trying to learn how to use AI systems. The more we talk to them, the more weird and wonderful things we learn about how they ‘think’. LLMs are a generative technology which makes them unpredictable at times.

But using AI for business, we need to be able to control parts of what they do. We built Fin Guidance to do this, so you can guide Fin. But guidance is like advice, you can give good or bad advice, and so you can give good or bad guidance!

And we’ve seen customers doing this, trying to give good guidance but learning through trial and error that it doesn’t quite work as intended. So we’re now building tools to help our customers write good guidance. This is cutting edge stuff, we’re using Anthropic’s Claude 3.7 Sonnet with Extended Thinking.

February 2025

Real time Inbox Translations

Customer Service teams need to support their customers in many languages, and so end up hiring multilingual speakers, using different translation tools, and ultimately adding a lot of complexity to their support operations.

But AI is excellent at real time translations. So we’ve been building that into the Intercom Inbox. Now any customer and any agent can seamlessly converse, no matter their language.

Fin over API

So far, Chat has been the dominant interface for us to communicate with AI. Makes sense, it is familiar. But that is going to change, and soon. We’re seeing customers who want to build their own interface to Fin (our AI Agent) so we’re building Fin over API. Now, any interface is possible.

Giving Fin Guidance

When Support teams hire new people, they train them, they give them guidance on what to say and how to react in different scenarios.

They need to do the same for AI Agents, so we’ve been building that into Fin.