Fin

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. 

We've been using Fin for about 6 months and genuinely love it — but the analytics drive me crazy.I can see our resolution rate is 71%. Great. But when my manager asks "why isn't it higher?" I have nothing. Which topics is Fin struggling with? Did that KB article I wrote last week actually help? No idea.We ended up exporting conversations manually and doing our own analysis in spreadsheets, which is... not ideal.How are other teams handling this? Are you just accepting the top-line number, or has anyone found a good way to actually dig into where Fin is failing?Would love to know if there's something I'm missing in the native reporting, or if everyone's just cobbling something together.

One of the main problems we’ve found with our Intercom chatbot is that it waits for the user to ask a question first - its reactive and passive.  We all want to solve software adoption and bring each user to value instantly - we believe you can achieve this by feeding your Intercom real-time user events so it can guide each user proactively to value. Copilots today face the following problems:Users don’t know your software so they don’t know what to ask. Users don’t always seek help when they need help and stay in limbo. Because they don’t know your software they may prompt in the wrong way and steer the conversation in the wrong direction. Therefore we think that if the chatbot had an additional real-time data source of what the user is doing the above painpoints could be solved. We’re iterating on this

Please make the customer name in Fin’s greeting bold, so it matches the rest of the message formatting. Right now the greeting can show the name in plain text while other text is bold, which looks inconsistent. A screenshot of the current behavior is attached. 

When a Banner is active in Intercom, teams should have the option to make its content available to Fin as a knowledge source. When the Banner is paused or deleted, that content should be automatically removed from Fin's knowledge base without any manual steps.The problemBanners are commonly used to communicate important product changes, outages, or announcements. In practice, many customers dismiss or skim banners without fully absorbing the information. This generates avoidable support volume — customers contact support asking questions the banner already answered.Fin has no visibility into active banner content today, so it cannot answer these questions accurately or consistently, even when the information is current and relevant.There are existing workarounds — such as creating a snippet or article with the same content — but these require manual cleanup after the banner is removed. Without that cleanup, outdated information remains in

Curious how others are approaching Monitors and scorecards in Intercom since the release. What types of conversations are you flagging? How are you structuring your scorecards? What criteria are you using to evaluate performance? How are you using the results once you have them?What’s been genuinely useful for your team so far? 

Has anyone experienced different responses when using batch test over preview? I feel like it does not have access to my full configuration like its persona. For example, I have renamed my Agent, but it will still refer to itself as Fin.

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...

Hi community 👋Has anyone found an effective way to handle customers who open a conversation by simply typing “agent”, without giving Fin / the AI Agent a chance to help?I’ve tried:general guidance encouraging self-serve first (minimal impact), and enabling “Set expectations for human support”, which unlocks “Ask for information before handover.” However, in our case the bot does ask a follow-up question, but then hands off to a human agent before waiting for the customer’s reply.What I’m looking for is a smarter approach (likely via guidance/behavior rules) where, when someone just types “agent” up front, the bot:probes for key details first, attempts to answer appropriately, and only escalates if it can’t be resolved.Any best practices, example setups, or wording that’s worked well for you would be hugely appreciated

Hi,I have written a data connector that will clear all logged in sessions from our own system. This works fine and fin uses it correctly based on the description in the data connector.However, since this will log the customer out, is there a way to get FIN to ask the user for confirmation before running the data connector?Example conversation:Customer: I cannot login, the phone app keeps trying to login, failing and going back to the login prompt.Fin: OK, I can try clearing our data cache, this will clear all logged in sessions? Are you sure?Customer: YesFin - *runs data connect* - can you try logging in again

Our workflows are fully set up in a non‑English language, with auto‑translate turned off. Fin detects the user’s language correctly, and the reply buttons display in the intended language — but the message text itself is being translated into English for the end‑user.From the backend side, the workflow appears completely normal in the language it was created in — the issue occurs only customer‑facing.This issue is currently preventing us from rolling Fin out in all 7 of our support languages, even though we’re very satisfied with Fin’s performance in English so far.Intercom support confirmed our setup is correct and has logged an internal ticket, but priority depends on whether others are affected.Is anyone else experiencing this?Would be great to know if this is impacting other workspaces too.Thanks! 🙏Ticket I

I want to be able to use the API to search for conversations with a certain CX score within a particular date range. Can you please add CX score to Accepted-Fields? https://developers.intercom.com/docs/references/rest-api/api.intercom.io/conversations/searchconversations#section/Accepted-Fields

Hi Intercom team,I’m integrating @intercom/intercom-react-native into a React Native 0.81.4 + Expo (prebuild) Android app, and I’m seeing an issue where new messages are not delivered while the Intercom conversation screen is open. They only appear after I navigate away and come back.What I’m seeingI open the Intercom Messenger from my app (using Intercom.present()). I start a conversation and stay on that conversation screen. From the Intercom workspace, I send a reply to that user. Nothing appears in the conversation UI while I stay on this screen. If I: go back to the previous screen and reopen the Messenger, or sometimes background and foreground the app then I suddenly see the new messages. So it looks like the real-time updates / polling are not happening while the conversation screen is active.Setup detailsReact Native:

How does your team measure Fin AI performance?We're trying to understand how different teams think about this. When you review Fin's performance, what signals do you actually look at?- Resolution rate vs. target- Handoff rate- Reopened conversations- CSAT on Fin interactions- Something else entirely?And when Fin underperforms, how do you diagnose why — do you have a process for that, or is it mostly manual conversation review?Would love to hear how others are approaching this.

Hi everyone,I’m looking for some guidance on best practices for using Fin with a knowledge base that supports multiple products within the same platform.Our platform now has three core product areas, and we’ve structured our knowledge base to reflect that. Shared tools are documented as a single canonical “source of truth” article, with product specific context pages that explain how that tool behaves within each product and link back to the canonical guide.This hub and spoke structure works well for humans navigating the knowledge base, but I want to make sure Fin is also responding with the correct product context when a customer asks a question. The challenge is that some tools and terminology overlap across products, so if a customer asks about something like the email tool, the correct guidance depends on which product they are using. We want to avoid a situation where Fin surfaces guidance from the wrong product area simply because the t

Hi everyone 👋We’re currently exploring how to automate our carrier loss/damage claims workflow using Fin AI and would really value input from anyone who has implemented something similar.ContextWe manage parcel claims (e.g. Royal Mail and other carriers) on behalf of merchants. Today, this process involves significant manual review, validation, routing, and follow-ups. Our goal is to reduce manual workload while maintaining a strong audit trail and strict compliance with carrier policies.What we’d like to automate: Collect structured claim data (tracking number, order number, carrier, reason, invoice, proof of sale, damage photos, etc.) Validate required fields and supporting documents Dynamically enforce carrier-specific rules (claim windows, liability caps, required evidence) Route complete claims to the right internal team or BPO

We are currently attempting to test deployment of Fin for Zendesk Messaging and are encountering some issues where the Zendesk messaging widget is blank. We have tried multiple audience configurations with no luck.Why is the widget blank despite seemingly meeting the audience conditions and the deployment of Fin being live? Example of a conversation log in Fin of this:   When someone does not match the audience for Fin, shouldn’t they still experience the Zendesk Messenger/AI Bot or are they completely locked out of any messaging experience?

Our team hit 71% resolution rate with Fin last month. Looked great on the surface — but when we dug in, we had no idea which topics were dragging it down or what to actually fix.Intercom shows you the overall number but nothing underneath it. No topic breakdown, no trend over time, no way to know if a KB update actually moved the needle.Curious how other teams handle this. Are you exporting conversation data and analyzing manually? Using a third-party tool? Or just accepting the top-line number and moving on?(I've been building something to address exactly this — happy to share early access if there's interest.)

I want to be able to check if making a change to content will improve Fin’s answer to a question without first having to publish it. Is there anyway to do this? 

I just published a new Support Stack Solo episode showing how I built my first Fin Procedure inside Intercom.Instead of just answering questions, this procedure turns Fin into a qualification concierge for my website. It asks a few questions, stores attributes, scores the lead, and routes them to the right next step.If you're experimenting with Fin Procedures or AI workflows, this is a practical walkthrough of the full setup (including what broke during testing).Watch it here: Support Stack Solo E03: How to Build a Fin Procedure in Intercom (Real Qualification Concierge)

 I’d like to request assistance with turning off the image replies feature for our Fin AI Agent. Currently, Fin automatically includes up to three relevant images/GIFs from our support content in its responses, but we'd prefer to have text-only replies.I understand this isn't a self-serve setting and requires support assistance to disable. Could someone help us turn off this feature for our workspace?Thanks for your help! 

Fin Voice: Option to view what document or guidance the Fin Voice is using when answer the clients inquiry (same with email and chat). 

Ability to Rearrange Guidance. Make this section movable. This will help us Manage the old and new guidance better.  Put an alphabetical option Include created by date or by person for better visibility (aside from change log) but change logs disappears. Ability to rearrange by drag and drop so that we can make related guidance close enough for visual control.

Is there a way that FIN can be instructed to go to certain "Paths" within the workflow or it's just a dead-end when we let FIN handle it?  I noticed that when a user goes into the “Let FIN handle” node, there is no way out. The only option is to escalate/hand it over to a human agent. 

Hello - I want to connect FIN AI to my status page that is hosted on Atlassian. For this im using, I plan on using the Procedures feature and create a new connector.I need to make an API connection to a specific endpoint from Atlassian - does anyone has any recommendation on which endpoint I could use from Atlassian? Does anyone has the same setup. Any guidance is much appreciated. Thanks