Fin

I would love to have an option to involve in only for collecting conversation Attributes. Right now it is not possible and any workaround works.  Even if I create a special tag/inbox for collecting attributes Fin must be involved which means even if it meet the escalation rule, it will reply that the conversation has been passed on. I would like Fin working in the background, collecting attributes from ALL conversations.  Maybe managing the Fin’s steps (in Let Fin handle nod in workflows) would be a solution. I mean turning off using content, guidances and leaving just collecting attributes would do the trick.  

When I checked the Japanese inquiries in Fin AI's Performance, I found that all the content is displayed in English even though customers wrote in Japanese. Can you change it to as it was written?Also, could you add a feature to filter and select only Japanese customers?When I search in Japanese in the content from Knowledge, the relevant items do not appear in the results. As my customers use only Japanese, I would really appreciate if you could solve this issue. Thank you.

I am currently setting up the Fin AI Agent. I have a question regarding the "Talk to a human" flow.When a user triggers the handoff to a human agent, how are the notifications handled for the assignee (or the team inbox)? Does the assignee receive an immediate email notification? Is it purely an in-app notification/browser push? I want to ensure that when the AI hands the conversation over, our support team is alerted immediately, even if they aren't staring at the Intercom dashboard.Thanks in advance!

Today we noticed an issue with Fin failing to respond to tickets. There have been no changes to the workflow but for whatever reason it just hasn’t responded to queries. We noticed the increase in FRT and drop in involvement but looking back we are almost certain this has happened before. It appears to be intermittent and no real obvious answer but curious if anyone else has experienced this and how you resolved. 

I’ve noticed FIN closing some conversations because the user didn’t explicitly confirm escalation, even though the conditions for escalation were met. The rules I set were: Escalate if the user shows negative or neutral sentiment. Escalate when the user provides all required information. Escalate when the user requests escalation. The issue is that when a user provides all the information and FIN sends the escalation message “An agent will be with you soon,” it later follows with “Is there anything else I can help you with?”If the user responds with something like “No,” FIN ignores the first escalation message and treats the user’s “No” as a signal to close the chat. Instead of keeping the ticket open for an agent, it ends the conversation.

Issues:Once you add a content to a missing one and create either a snippet or article from it- you can never go back or see an audit trail of what you have actually done.    There is no list anywhere where you can see which content gaps you have actually optimized. We would like to store them somewhere which them might be helpful for configuting another area   Once you add the content and hit save, it opens the next suggestion instead of taking you back to the Optimize page, this is quite confusing and unrelated from what you were doing.    No export buttons anywhere   There is a table where they give percentages of conversations, but you can not clic

Hey Community,we have issues setting up Intercom AI so it solves different Topic automatically. Can you help us?For some reason FIN suddenly and randomly answers with wrong answers.We tried everything (with and without guidance,...) All the Content stayed the same and in the past FIN was super helpful. We are looking for an expert to help us automate different Topics in our Customer Support.Thank you in advance!

My company is anxiously awaiting the ability to access Fin through a channel API in our own bespoke messenger. Are any of you already doing something similar? If so, how’s that going?

Hi Community! We are still newish to Intercom, launching in earnest in April of 2025, and have been slow-rolling it out to our users. We currently have Fin enabled for ~100 of our customers, with plans to double, then triple that number in the upcoming weeks.Overall, Intercom has been great and Fin is performing even better than our initial expectations. That said, the one reoccurring issue we continue to see is users shortcuttong/circumventing Fin--when the chat starts, their first question is “Talk to a person” or “create a case,” and since Fin is frictionless, he will not fight them and defers to the case handover process (we use ServiceCloud). Issue is, since no question or context is present, none of the AI-detection fields fill in, and the case just is sent to a ‘triage’ queue until our reception team can reach out to determine what the users’ question/issue was so they can then place them into the correct Support queue (we do not currently offer live-cha

Fin is connected to my work Instagram business page. A follower recently tagged me in a story (which I received as a DM), and Fin is answering that DM. How do I stop that from happening?

Hi there,We’ve implemented Fin AI (Chat and Email) on our support desk, and it’s been fantastic so far—it’s doing a great job handling first-line queries! 😊However, we’ve noticed a challenge when a customer submits a vague message. Fin will respond with technically correct information, but it’s often not relevant to what the customer truly needs.I’m wondering if it’s possible to improve this by getting Fin to ask clarifying questions before responding. I’ve been advised to set up a new workflow where specific vague questions prompt Fin to ask follow-ups, but trying to predict and account for all the potential vague queries customers might come up with feels inefficient.Is there a better way to manage this? Any advice or insights you could share would be hugely appreciated!Thanks so much

I have converted my Conversation attributes for issue types to Fin attributes using the UI workflow. I have an “Other” attribute set with the exact wording that Intercom fin suggested in case it couldn’t detect any of the others from my descriptions. I have them enabled for all audiences. I have a very simple workflow that starts with a user typing and branches to Fin answering. The audience is ‘custom → logged in users’. → What brings you here today? Let customer type → Let Fin handle → If escalated show reply time. When I send fin a message it finds the correct articles and guidance, but there’s no indication it’s detecting any of my attributes as the conversation log does not show the event and the attribute is not set on the conversation details panel. I turned on Urgency attributes to see if it would detect those as a test and it is not detecting them until the ticket is closed, which I think defeats the purpose. But at least I can see a log of when it dete

Hello,I want to add Intercom remote MCP to an AI agent. How do I add my callback URI to the allow list for the remote MCP?Thanking in anticipation.

Hi there! I’m trying to test a use case, but no luck so far, so I wanted o see if any of you tried something similar. Use case: I need Fin to override the user’s initial inquiry IF Fin detects a Health check issue on the user’s account. I have the data connector set up, and I added a When/If/then guidance. So far, this guidance is only triggered if the user asks a direct question about their account health status. Here’s a screenshot of the rule:  

Is there a way to have the Fin AI agent reference information (including hyperlinks to PDFs) on a website but restrict it from linking customers to the site? We have a page with links to user manuals for devices listed on our website that was meant to just be for AI reference rather than for public consumption. We want Fin to be able to answer a question troubleshooting use of a specific device type with the user manual, but don’t want to take customers to a page with a huge table of devices on it.

Whenever Fin receives a negative rating from a customer, I review the conversation and decide if perhaps it should be escalated to a human, or make improvements to our content. Are there any suggestions for automating this process? Or reports that tell us why there was a DSAT rating specifically (outside of the CX score)? Or perhaps a section in Optimize that will show us content suggestions specifically linked to a DSAT outcome? 

Hello! I wanted to report a couple of issues we’ve been experiencing with the FIN Suggestions feature: Suggestions tab showing empty results – We sometimes see that a suggestion appears to be available, but when we open it, it’s actually empty (no comments or text). Article changes not saving – When trying to edit an article through FIN Suggestions, we often get an error saying the changes could not be saved. In some cases, the changes aren’t even saved as a draft, which has caused us to lose work and time. Could you let us know if these are known bugs or if there are any current workarounds?Additionally, we were wondering if there are any options to guide or rate suggestions so the system can learn from our feedback. At the moment, many suggestions seem repetitive and often just reword content without explaining why the original version might not be good. It would be great to have a way to indicate which suggestions ar

We have setup intercom as our helpdesk for our Shopify ecommerce business. Customers who are logged in to their shopify account are getting excellent replies from FIN, with order information etc. But when a customer chats to FIN and they are not logged in, they only get generic knowledge center information. What is the best workflow / solution to make sure Visitors log into shopify before chatting?Can FIN prompt the user to log in at the start of a visitor chat? Can FIN authenticate the user just with the email / order number? We’re also looking for someone to review our whole setup and offer some improvements, please get in touch if you can help us out. Thanks! Scott 

Hi Intercom Community,I’m trying to fine-tune how FIN handles unresolved issues. Specifically:Is there a way to set a limit on how many times FIN tries to resolve a customer’s question before escalating? Can FIN automatically hand off to a human agent after those attempts?I want to make sure customers aren’t stuck in a loop if FIN can’t help. Ideally, it would try a few times, then gracefully pass the conversation to a person.Has anyone set this up successfully? Would love to hear how you approached it—or if there’s a built-in way to do this.Thanks in advance!—Vanessa

Hey everyone 👋We’re currently using Fin as the first line of support, handling all incoming customer conversations.It works great — once a human agent joins the conversation, Fin automatically stops responding, which makes perfect sense in most cases.However, there are many situations where the agent realizes that Fin could actually continue handling the customer effectively after their short intervention.It would be super helpful if agents could reactivate Fin in a conversation — ideally with a simple button or command — so Fin can pick up right where it left off.Is there a way to do this today? If not, we’d love to see this added as a future feature 🙏Thanks!Tamir

Hi all, we’re pretty new to Fin AI & chatbot setup in general, so we might be missing something, however, I’m seeing massive differences in how Fin responds to questions in the Preview environment versus the actual live environment on our website.As an example – one of our users asked a fairly basic question about our service, and Fin AI responded with “Sorry, I couldn’t find information related to your question.” However, when I pasted the same question into the Fin AI preview (logged in as an organizational user within the Intercom admin dashboard), it returned a comprehensive response and fully answered the user’s question.Currently, we have Fin AI enabled for all Users, Leads, and Visitors via Intercom Messenger only, and have it trained on all of our published support articles, as prompted via the Simple Deploy process.I’ve scoured all available Fin AI settings within Intercom to no avail, and I’m not able to find another community thread about this top

i was trying to create an account but after signing up i got this 403 Forbidden: Workspace Suspended

My teammates reported an issue with a Fin response that stemmed from a Guidance prompt that was never enabled. I spent lots of time testing our active prompts before opening the prompt that isn’t enabled. That prompt is where Fin was pulling from; I had to delete the prompt entirely so Fin wouldn’t use it. How can I ensure that draft prompts are not being used in the background? 

We utilize Fin as the first line of defense in supporting our software. I’d like to explore having Fin handle chats related to known bugs/issues. Right now, a user will message saying “I’m experiencing XYZ issue” and Fin will go through the normal troubleshooting steps. Ultimately these chats often get routed to a human agent who then lets the user know we are aware of the issue and working on a resolution. Users are often annoyed that they had to go through the process of explaining the issue to Fin just to find out we knew there was an issue. Sometimes these issues only impact a small subject of our user base so we don’t want to widely exclaim that there is an issue. Thoughts/Questions:Best way to implement something like this - I’m curious if we can utilize the Content and Sources (beta) section under Guidance? Best way to track these conversations - we track these reports so we can reach back out to the user once the issue is resolved. Ideally, these

I’ve learned from Intercom’s documentation that CX scores are calculated using three signals: Customer sentiment, Resolution status, and Service quality.When I want to understand why a conversation has a certain CX score, the single blended number doesn’t always give enough detail. For example, was it customer sentiment that drove the score down, or did resolution status carry more weight?Is there a way to see the score for each of the three signals individually, rather than just the overall CX score? Having visibility into the individual components would really help in analyzing conversations more deeply and understanding what’s driving the overall CX score.