Fin procedures: A practical guide for customer support teams

Customer support isn't what it used to be. Your team is probably dealing with less "how do I reset my password?" and more complex, multi-step problems that jump between different apps. Think checking an order in Shopify, then processing a refund in Stripe, all in one conversation. The real question is how you handle all this without overwhelming your support agents.

This is the problem AI "procedures" or workflows are meant to solve. They're designed to automate the complicated, step-by-step tasks. One of the most talked-about options comes from Intercom, called Fin procedures, which is built to take on these tricky support requests.

But what are they, really? And are they the right move for your team? This guide will give you a straight-up look at what Intercom's Fin procedures do, how they work, where they fall short, and how they compare to more flexible tools that aren't tied to a single platform.

What are Intercom's Fin procedures?

Intercom's Fin procedures are a feature of its AI agent, Fin. You can think of them as a playbook you give the AI to handle customer issues that need more than a simple, one-off answer. They’re for situations that involve a bit of business logic, a check-in with another system, or an internal approval step.

They're an update to Intercom's older "Fin Tasks" and are supposed to be more powerful and easier to build using plain English. With Fin procedures, you can:

• Set things up with natural language: You can build a workflow by just writing out instructions, kind of like you'd write a standard operating procedure (SOP) for a new hire.

• Use rule-based control: You can add specific rules, like if/else logic or even small bits of code, to make sure the AI follows a precise path. This is great for things like checking if a customer is actually eligible for a refund or a subscription upgrade.

• Let the AI handle interruptions: The AI is smart enough to adapt if a customer goes off-topic, asks a new question, or interrupts the process. It can handle the side question and then get back to the right step in the procedure.

• Connect to your other systems: Fin can link up with other tools your business uses, like Stripe or Shopify, to pull information or take action.

A closer look at how Fin procedures work

When you get into the nitty-gritty, you'll find a powerful system that can also get pretty complex. Here’s a breakdown of what it takes to get Fin procedures up and running.

Training and setting up your first Fin procedures

Getting started means telling Fin what to do. You can write instructions from scratch, copy and paste an SOP you already have, or ask the AI to draft a procedure for you based on a simple outline.

A screenshot showing the workflow builder in Intercom, where users can set up Fin procedures.

There's a bit of a catch, though. According to Intercom’s own documentation, Procedures are in "managed availability," and a successful launch often needs "hands-on setup support." While the tool is capable, this suggests it’s not something you can just switch on and use immediately. For many teams, this means a slower start and a heavy reliance on Intercom's own team, which is a big departure from platforms designed for a self-serve setup you can get going in a few minutes.

Mixing flexible AI with rigid rules

The interesting part about Fin procedures is how they mix conversational AI with strict, rule-based logic. Let's say a customer wants to make a return. The AI can have a normal, friendly chat to figure out why. But when it's time to check if the purchase is within the 30-day return window, a hard-coded rule takes over to calculate the date and give a firm yes or no.

This combination gives you a lot of precision. The downside? It can add to your maintenance pile. Managing code snippets and branching logic paths requires some technical know-how, which might create a bottleneck if your support team can't make adjustments on their own.

Testing and validation with simulations

Before you let your new AI loose on customers, you need to be sure it works. Intercom has a "Simulations" feature where another AI pretends to be a customer, running through a procedure to see how it performs. It's a necessary step for catching bugs and making sure your workflows are solid.

A screenshot of Intercom's simulation feature for testing Fin procedures.

While testing a new workflow is helpful, what's even better is seeing how an AI would perform against problems you've already solved. Simulating an AI agent on thousands of your actual past tickets gives you an immediate, real-world forecast of how many issues it could resolve. This helps you figure out which topics are perfect for automation before you even write a single line of a procedure, saving you a ton of time.

Key limitations of a platform-specific approach

Fin procedures are definitely capable, but their biggest weaknesses come from being locked into a single platform. Here are a few big limitations to think about before you commit.

The high cost of being locked in

The number one issue is simple: Fin procedures only work inside the Intercom ecosystem. This might not sound like a huge problem if you're happy with Intercom now, but what about a year or two down the road?

What happens if your company grows and decides to switch to Zendesk for its better routing features? Or maybe you move to Freshdesk to keep all your tools in one place. In either scenario, all the time and effort you poured into building and fine-tuning your Fin procedures is just… gone. You have to start all over again. This is a classic case of vendor lock-in, where it becomes so painful to leave that you feel trapped. An AI layer that works with your helpdesk can move with you as your tech stack changes.

Working with scattered knowledge

Fin can connect to other systems to look up things like order details, which is good. But its main "knowledge" is often built from SOPs and conversations that live only inside Intercom. Most teams don't work in a bubble, and their AI shouldn't either.

A diagram illustrating the difference between siloed knowledge sources in a single platform versus unified knowledge from multiple sources.

Your team's real knowledge is probably spread all over the place. It's in project plans in Google Docs, technical guides in Confluence, and quick troubleshooting threads in Slack. An AI agent that can't tap into this collective brain is at a serious disadvantage. A truly helpful AI should pull knowledge from everywhere your team works to give the most complete answers.

Vague pricing and unpredictable costs

If you try to find a price for Fin, you won't. Intercom doesn't publish its pricing for Fin or its other advanced features. To get a number, you have to talk to a sales representative.

This lack of transparency has real business consequences. The process is slow, it’s almost impossible to predict what you'll spend, and it creates friction from the very beginning. You can’t easily compare your options or budget properly without getting on a sales call. This is a world away from modern software tools that have clear, public pricing and let you start without a mandatory demo.

The alternative to Fin procedures: A universal AI layer for your entire support stack

Instead of locking your automation into one platform, another way to go is to use a universal AI layer that plugs into your existing tools. This is what tools like eesel AI are all about. It’s built to be flexible, self-serve, and connected to your entire knowledge ecosystem.

Feature	Intercom Fin Procedures	eesel AI
Platform Dependency	Intercom only	Works with Zendesk, Freshdesk, Intercom, Jira & more
Setup Process	Requires demos & "managed availability"	Fully self-serve; go live in minutes
Knowledge Sources	Primarily SOPs & Intercom data	Unifies knowledge from Confluence, Google Docs, past tickets, etc.
Testing Method	Simulates newly built workflows	Simulates performance on thousands of actual past tickets
Pricing Model	Custom; requires sales call	Transparent, public pricing with a free trial

Here’s what makes this approach different:

• Get started in minutes, not months: eesel AI has one-click integrations and a truly self-serve setup. You can skip the required demos and long sales calls. Just connect your helpdesk, point it to your knowledge sources, and start seeing results almost immediately.

• Unify all your knowledge, instantly: It learns from your team's collective wisdom, no matter where it is. It can pull context from a Google Doc, a Confluence page, or past ticket resolutions to answer questions accurately. It’s not just following a script; it’s using your entire knowledge base.

• Test with confidence and full control: Remember being able to simulate on historical tickets? eesel AI lets you do exactly that, giving you an accurate forecast of resolution rates before you automate a single ticket. It also gives you precise control to decide which types of questions to automate, so you can start small and grow from there.

Intercom Fin procedures pricing

As we mentioned, Intercom doesn't list prices for its advanced AI features like Fin procedures on its website. Access is usually bundled into their higher-cost plans (like Pro or Premium) or sold as part of a custom package. To get a price, you have to schedule a call with their sales team.

This makes it tough to plan and budget. In contrast, solutions like eesel AI offer clear and predictable pricing. All plans and features are listed publicly on the website, and you can get started on a flexible monthly subscription without being stuck in a long-term contract.

Choosing the right automation for your team

Intercom's Fin procedures are a powerful, native tool for automating complex customer questions, but they come with a big trade-off. They make the most sense for teams who are all-in on the Intercom ecosystem and have the time and resources for a hands-on, guided setup.

However, for teams that care about flexibility, getting started quickly, and the power of unified knowledge, a platform-agnostic AI layer is a much more strategic choice. It means your automation workflows aren't held hostage by your helpdesk, your AI can learn from all your tools, and you get the transparency needed to make smart decisions.

If you're looking for an AI agent that works with your tools instead of locking you into them, try eesel AI for free and see how fast you can start automating your most complex support issues.