Train Fin

Hi all,Looking for guidance on customizing Fin's default human handoff behavior (We use Fin over API).Right now, when a user asks for a human (Right from the first message), Fin responds with:"I understand you would like human support. Would you like me to connect you to a human agent? You can also continue working with me and provide more details if you prefer."We're building a multi-stage escalation flow (a short ladder of clarifying prompts before handoff) to collect 3 key infos for our support team (What customers were trying to do in the product, where are they in the product, what happened), but we need the final stage to first check whether the user already gave issue details earlier in the conversation, rather than asking for information a third time if they already provided it. I understand that Escalation Guidances are stateless so we can’t store anything in there. How can we build a robust support detail collection flow in case customer asked directly for human agents? i.e (

With Fin for Sales, we aren't using the meeting booker integrations for qualified sales meetings. Instead, we route prospects with the gCal app to schedule meetings with sales reps based on territory. One limitation we've encountered is that we haven't been able to set the meeting owner to a field that syncs with the Salesforce record owner. How can this be made possible?

Can Fin read customer order forms sent by email as PDF attachments, including ones with complex or multi-column layouts, and convert the data into a standard JSON format? If not, can we use a workflow or integration in Fin to reliably process these documents and ensure the final output is in JSON format?

Fin reads phone numbers too quickly Request: add a setting to slow down or format phone number delivery

When Fin replies or send a follow up for inactive customers, the outbound reply doesn't include the quoted thread below the message. Recipients only see the reply itself with no prior context.Is there a setting in Intercom to enable quoted/threaded replies so the previous email history is included in outbound replies the way traditional email clients handle it? If not, what's the recommended workaround for managing external partner email threads through Intercom without losing context for recipients?

We're trying to get Fin to behave differently depending on when the customer asks for a human. We've tested two separate guidance rules but it's not sticking. Anyone solved this?Here’s what we want to do:First message = "offer" escalationCustomer says "representative"? Fin should hit them with: “Would you like me to connect you with a human agent? Or if you tell me what you're looking for help with, I'd be happy to try assisting you first.”(Reason: Let Fin actually try to help before bouncing them out)Mid-conversation = "escalate immediately"Customer says "representative" after you've been chatting? Skip the offer—just connect them. No questions asked.(Reason: They're probably frustrated and have already interacted with Fin. Don't want to make them explain twice.) 

I'm looking for suggestions on how to organize Help Center articles and knowledge base content so users can quickly find the information they need. Do you prefer organizing content by categories, user intent, or product features?While researching content structure and user engagement, I came across a resource about baby care products that does a good job of presenting information in a clear and easy-to-navigate format. I'm interested in learning what strategies others use to improve content discoverability and user experience.

Hey all!I’d been exploring this using Fin but had hit a road block and wanted to see if anyone had created anything like this:We want every negative Fin CSAT to create a ticket to our team to review to see if we could make any changes to Fin.We use a reusable workflow to route negative Fin CSATs to the team - and we want that to continue - but in the background we want this ticket to route to a different team to review. Any thoughts? My first post here, so let me know if not the right format.

I find the in app Fin experience on intercom to be incredibly helpful and I use it all the time. However, I get so many “rate your conversation” emails that it is starting to get annoying. Is there a way that I can mute these? To be clear, this is my as an intercom user using the in-app Fin to ask intercom related questions. Thanks!

Hi everyone,We’re trying to build an Intercom Data Connector that retrieves customer-specific data from our backend.Our backend API requires a user-specific access token. This token is generated only after the customer completes an OTP/authentication flow, and each customer receives a different token.The flow we want to support is: The customer completes OTP authentication. The OTP/auth connector returns a response containing: { "data": { "access_token": "..." }} A second connector should then call our recommendations API using that token in the Authorization header: Authorization: Bearer <data.access_token>The issue:When we try to pass the token dynamically in the connector header, for example:Authorization: Bearer {{accessToken}}or by using a value returned from a previous connector/action, our backend does not receive the Authorization header/token.The only setup that worked was using Intercom’s Authentication Token feature with a static Text token. However, this does n

Ability to Export Guidance. Manually gathering guidance from 7 workspaces is too time consuming. 

We have customers that answer no multiple times to Fins questions of ‘Did that answer your question’ or similar. They will say ‘No’ and rephrase their question but Fin still can’t answer it correctly. Does anyone have any recommendations on how I could get it to ask if they want to speak to a human after the 2nd time of saying ‘No it hasn’t helped’

Can we better contextualise Help Centre content for Fin?For example, having internal-only guidance/instructions embedded directly within articles that end users cannot see. While content/source guidance and snippets help, they become difficult to scale when managing thousands of articles and hundreds of supporting snippets.In our case, Fin’s errors are often less about incorrect content and more about misunderstanding nuance or scenario context. Being able to add contextual instructions, edge cases, or operational guidance directly alongside the article content would make maintenance significantly easier and likely improve response quality.

We use the “Other” guidance heavily for our platform and voice isn’t supported yet. Wondering how other people have worked around this? I tried to update our FAQs as much as possible but there has been issues in which our Fin voice keeps repeating the wrong thing that would have worked in chat or email because of Other guidances set in place. 

Something is going wrong with my anti-repetition guidance. No matter what, Fin will not stop repeating/rephrasing the same answer multiple times. I have guidance on asking clarifying questions and am wondering if that’s part of the issue. My adjustments to clarification guidance also aren’t making things better. Using optimize and other ai tools isn’t helping.I’m stuck and am a team of one. If you have any suggestions or examples that work well for you, please list them here!

We have a number of products with a lot of overlapping terminology, and a lot of audiences that overlap with other audiences. This has made it difficult to target the information Fin uses very specifically. We have been considering setting audiences up using conversation data instead of just user data, but I’m having a hard time understanding if/how that would work. We have a new conversation attribute that would be selected and help define the audience for that conversation. But is that effective? If the customer asked another question in the same conversation, or had chosen something incorrectly, could the audience for that conversation ever be changed? Open to any suggestions here on how this could work, or what better options might be. 

Fin AI will always give suggestions when a customer asks a question. Let’s say the customer asks about a device (we have physical products that require a little technical knowledge), Fin AI always responds something along the lines “What do you want to know? (for example: this thing, that thing, many other things) You might be able to do this or that”I would like to to answer the customer’s question and not give extra information unless absolutely relevant. However, no matter what guidance I give, it will not stop this behavior.

Hi everyone,We’re using Fin in Hebrew, but we keep seeing cases where Fin adds random English words inside Hebrew replies, even when those words do not appear in our Help Center articles or snippets.We also had a more serious case where Fin inserted Japanese/Chinese-looking characters into a Hebrew customer-facing reply.We already added clear Guidance telling Fin to reply fully in Hebrew and avoid English unless it is a brand name, URL, product name, or a required term. The issue still happens.Intercom Support suggested using Guidance and mentioned the multilingual glossary, but also clarified that the glossary does not apply to AI-generated replies.Has anyone using Fin in Hebrew or another non-English language found a reliable way to prevent this?Is this something Guidance can actually solve, or is this a current limitation of Fin?This is affecting customer trust, so any practical advice would be appreciated.

Hi All, How do you all work around the guidance limitation of 100 pieces of total guidance? We have the opportunity to consolidate some guidance, but because the bot is used across multiple teams with different workflows and channels, this limitation will hamper us. Is there a way to increase the limit?  What alternatives do y’all use to guidance to achieve the same outcome?  How many pieces of guidance do y’all have? Thanks!Afton

I have a very simple use case. I want Fin to ask for the Project and the Organization before it escalates. For some reason, Fin continues to frame it like this:“Would you like me to connect you with a human agent to assist further? Or if you provide more details about your project and organization, I can continue to help you.”No amount of escalation guidance refining is working. Fin should be able to handle this, no?   

We have 100+ physical audio technology products (along with manuals for all of them). Additionally many of them have similar names. First, we need Fin AI to differentiate these products. Second we need to have Fin AI be able to do troubleshooting and give product recommendations. What would be the best practice for getting Fin AI to differentiate our products, and not make any up.Additionally, for troubleshooting, are we best off letting Fin-AI just try to handle it, or should we create procedures that run customers through their problem. Let’s say we choose procedures, how should I make sure Fin AI uses the relevant content (correct manual) for every device? 

I believe Fin is great when it answers from connected docs, but it gets a lot better when it can see what happened before the user opened chat. I am looking at three ways to make it more proactive:page/URL targeting in Workflows event-based triggers and real-time session context written into internal notes The real difference seems to be whether Fin only gets a trigger, or whether it also gets the product activity that explains what the user was actually trying to do.Curious how others here are handling this: Are you using URL rules, events, or session notes? What’s been most effective in practice? Any tips for keeping the thread readable while still giving Fin enough context?

At present Fin has a wide gap between confirmed resolved conversations and assumed resolved conversations. Our Help Centre articles are updated, it’s usually regarding more complex or personalised queries. Whilst some of the assumed resolved conversations are resolved, a lot of them are not. Is there a way to add in another follow up from Fin to check the resolution state and thus giving the user more time to respond to these. Moving forward it could be helpful to have inactive conversations to be escalated to a teammate so that the 'Assumed resolution' conversations can be automated within a workflow. From what I’ve been looking into it seems that a workflow on a customer being unresponsive can only start after a teammate reply rather than from a bot reply. When trying to set this up as an Attribute to route assumed resolved conversations to a teammate Fin just seemed to pass conversations along without trying to resolve them first.Any advice here would be appreciated - thank you!

A customer would reach out about a partnership and our Fin would rightly answer and suggest the customer reach out to partnership@, how sometimes the customers would then CC that email in the current conversation and Fin would not stop replying to both the customer AND someone from our company which looks bad. Is there a way to have Fin stop replying to the conversation if a customer CCs someone else? The only path I can think of is an escalation rule that would route to a human whenever someone asks about ta partnership, so Fin won’t even answer. 

We're using the Fin AI Agent on a Shopify store with only light integration to Zendesk (mostly using Fin to handle customer questions about our site, products, and policies via chat—no complex workflows or heavy ticketing yet). We have thousands of products in our catalog, and Fin keeps randomly suggesting or highlighting specific ones (e.g., naming a particular brand/model like "Check out the XYZ-5000" or "Look at this popular option from Brand A") while completely ignoring hundreds of other equally comparable alternatives. This leads to unbalanced, unintended recommendations that we don't want at all. I’d rather have them do their own search than be directed to several random options vs. the hundreds fully available, FAILED  I've tried instructing "Guidance" not to do this in every possible way to block this:Strong overrides like "CRITICAL RULE - OVERRIDE ALL OTHER INSTRUCTIONS: NEVER mention/recommend..." Direct "YOU MUST..." commands with ALL CAPS emphasis Concrete examples of acce