Fin conversation training: A 2025 guide to how it really works

AI agents are popping up everywhere in customer support, and if you're in this world, you've definitely heard of Intercom's Fin. It promises to handle conversations on its own, solve problems in a flash, and let your team focus on the trickier stuff. But hold on, before you jump in, it's worth knowing what's going on behind the curtain. An AI agent is only as good as its training.

Nailing the Fin conversation training is what separates a genuinely helpful assistant from a frustrating bot that just bounces tickets back to your team. In this guide, we'll walk through how Fin learns, its key features, and some big limitations you should be aware of, including its tricky pricing. We'll also look at a more flexible alternative for teams who want to stay in control.

What is Intercom Fin?

So, what exactly is Intercom Fin? It's Intercom's own AI agent, designed to handle customer support conversations right inside their platform. Think of it as your first line of defense: it reads customer questions and shoots back instant answers by digging through your help docs.

A screenshot of the Intercom Fin interface, illustrating the AI agent used for Fin conversation training.

Since it's an Intercom product, it's baked right into their ecosystem. That sounds great, but being locked into one system has its downsides, especially if your team uses tools from other companies.

How Fin conversation training works

Fin's performance comes down to how it's trained and the quality of the information it can get its hands on. The whole process involves connecting it to your existing content and then letting it learn from how your team has handled chats in the past. Let's break down the main parts.

Training on knowledge sources and past conversations

At its heart, Fin learns from the stuff you feed it. You start by connecting it to your help center articles, FAQs, and any other public documents. It reads all of that to get a handle on your products and common problems.

Recently, Intercom also started letting Fin learn from your team's past conversations, which they talk about on their training page. This helps it pick up on the little details of how your agents solve problems. But here’s a pretty big catch: this is an opt-out feature. That means by default, your conversation data might be used to train their models unless you manually go and turn it off.

For any company that's careful about its data, that's a bit of a red flag. It's a different philosophy from platforms like eesel AI, which are built to be private from the start. With eesel AI, your company's data is only ever used for your AI agent. It’s never shared or used to train wider models, which gives you peace of mind that your information stays yours.

The Fin Flywheel: Train, test, deploy, and analyze

Intercom has this four-step process they call the "Fin Flywheel" for getting the agent working. The idea is to keep making it better over time:

1. Train: You kick things off by connecting Fin to your knowledge base, internal guides, and conversation history.

2. Test: Next, you can try out Fin's answers in a safe space before it goes live with customers.

3. Deploy: Once you feel good about it, you can turn Fin on across your support channels like chat, email, and voice.

4. Analyze: Lastly, you look at its performance to see what's working and what's not, and use that info to improve its training.

It sounds good on paper, but that 'test' step can be a little underwhelming. You get a general idea of how Fin might answer a question, but you can't really run a large-scale test to see how it would have handled, say, the last few thousand tickets you received. That makes it tough to know what its real-world resolution rate will be before you set it loose on your customers.

Key features and limitations

Fin is definitely a capable tool, especially if your team is already living and breathing Intercom. But its power comes with some serious trade-offs that can become real roadblocks as you grow.

The "walled garden" limitation

The biggest hurdle with Fin is that it only works inside Intercom. That's it. If your team lives in a different help desk like Zendesk, Freshdesk, or Gorgias, you're out of luck unless you're prepared for a massive, expensive project to move everything over.

This is a classic case of vendor lock-in, and it can really paint you into a corner. You're stuck with their tools, even if another one might be better for a specific job. A more modern approach is an AI tool that plays nicely with what you already have. That's how tools like eesel AI are designed, they plug right into the help desk you already know and love. You get the benefits of AI without having to tear down your current setup.

Limited control and simulation capabilities

Fin gives you some control, but it can be hard to get really specific about which tickets the AI should tackle and which ones need a human touch. Most teams aren't looking to automate everything, just the simple, repetitive stuff.

And that's why being able to test properly before you go live is so important. As we mentioned, Fin's testing is pretty basic. You can't run a simulation on your past ticket history to get a solid forecast of its performance.

That’s a whole different ballgame compared to the simulation mode in eesel AI. There, you can run the AI on thousands of your actual past tickets to see exactly how it would have performed. You get a real report on its likely resolution rate and can tweak its behavior before a single customer ever talks to it. You launch knowing what you're getting into.

A screenshot of the eesel AI simulation mode, showing how teams can test their AI agent on historical data before deployment, a key advantage over basic Fin conversation training.

Feature	Intercom Fin	eesel AI
Help Desk Compatibility	Intercom only	Zendesk, Freshdesk, Intercom, Gorgias & more
Setup Process	Requires demos and sales calls	Fully self-serve, live in minutes
Pre-launch Testing	Basic testing environment	Advanced simulation on historical tickets
Automation Control	Broad, less granular rules	Granular control over specific ticket types
Knowledge Sources	Help desk, some integrations	100+ sources (Confluence, GDocs, Notion, etc.)

The hidden costs: Understanding Fin's pricing model

Beyond the features, the real sticker shock for many businesses is Fin's pricing. Its model can lead to some wild, unpredictable bills that are tough to plan for.

Fin's unpredictable per-resolution pricing

Fin's pricing is based on a per-resolution fee. Intercom says it costs $0.99 every time Fin solves a problem, and that's on top of your regular Intercom subscription.

Here's the kicker: the model basically penalizes you for doing well. The better your AI gets and the more tickets it handles, the more you pay. Let's say you have a busy month and Fin solves 5,000 tickets. That's an extra $5,000 on your bill you might not have planned for. This makes budgeting a nightmare because your costs swing up and down with your ticket volume.

A more predictable pricing alternative

This is where a different pricing model can be a lifesaver. Take a look at eesel AI's pricing for comparison. It’s all about being predictable. Instead of charging for every resolution, eesel AI has simple, flat-rate plans. You get a big monthly bucket of AI interactions (which covers both replies and actions), and that's it.

A view of the eesel AI pricing page, which offers a predictable, flat-rate model as an alternative to the per-resolution costs of Fin conversation training.

This means you know exactly what you'll be paying each month, which makes budgeting way easier. You're not dinged for having a high resolution rate, and you can often start with a simple month-to-month plan instead of getting locked into a long annual contract. For any business that likes to know what its bills will look like, a flat-rate model just makes more sense.

Is Fin conversation training right for you?

So, what's the verdict? Fin is a powerful tool, no doubt. But the way its Fin conversation training works, combined with its other limitations, creates some real headaches. The vendor lock-in, the basic testing options, and the unpredictable pricing make it a tough sell for a lot of teams.

Fin really only makes sense if you're already all-in on the Intercom ecosystem and you're okay with its pricing model and constraints. For just about everyone else, there are better, more flexible ways to get the job done.

A better way to automate your support

If you're looking for that flexibility, control, and predictability, something like eesel AI might be a better fit. It was built specifically to avoid the common frustrations you find with closed platforms.

Here’s a quick rundown of what sets it apart:

• Get up and running in minutes, not months: The setup is completely self-serve, so you don't have to wait on sales calls.

• It works with your current tools: It connects directly to the help desk you already use and over 100 other knowledge sources.

• Test with real data: You can see how it would have performed on thousands of your past tickets before you ever launch.

• You’re in the driver's seat: You decide exactly which queries get automated and how the AI responds.

• Clear, predictable pricing: Just a simple flat-rate subscription. No surprise fees for resolving too many tickets.

A workflow diagram showcasing the simple, self-serve setup process for eesel AI, an alternative to the more complex Fin conversation training.

Ready for an AI agent that works for you, not against you? Start your free eesel AI trial today and see how quickly you can automate support with confidence.