Train Fin

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

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 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

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

 In Ep. 11 of Support Stack, Gabriela Passeri (Knowledge Manager at AutoDS) walks through how they made Fin actually understand their product.Their key move was to build internal, Fin-enabled glossaries mapping customer language to product terminology. Including synonyms, “avoid confusion with”, and even UI layout guidance.Super practical and very applicable if you have a complex B2B SaaS product with integrations!Full episode: I really hope it helps! 

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

Increase Guidance Limit From 100 to 150 or more… Hello Team, we have reached 100 Fin guidance limit in total for Chat/Email and Voice. Can you separate this limiter instead? I mean...Like 100 for Voice and 100 for non-voice?Of can you just increase the limit to 150 if it’s easier to configure?  We are adding more features to as we go along the way. So, our other work space will surely reach the limit pretty soon. 

Fin is technically able to read dates, but in practice it often fails to reason about them correctly.ExampleFin currently sends out discount codes that are already expired, because it doesn’t reliably calculate whether a date is in the past, present, or future.Feature request    •    Fin should be able to compare dates to the current date    •    Fin should not mention or suggest expired offers    •    Ideally, Fin should be aware of:    •    “valid until”    •    “expired”    •    “not yet active”Why this matters    •    Prevents customer frustration    •    Avoids incorrect promises (e.g. expired discounts)    •    Increases trust in AI-generated responses 

I'm looking for a streamlined QA process for managing Fin’s performance as a one-woman team. Would love some suggestions for best practices for maintaining quality without getting overwhelmed with all the reports and data Intercom provides for Fin performance.

Hi everyone,Our bot communicates in Hebrew. Because Hebrew is gendered, we’re seeing an inconsistency: Fin sometimes replies in masculine form and sometimes in feminine form.Both of the following Guidance rules are under Communication style: Bot self-reference is always masculine When responding in Hebrew, always refer to yourself in masculine grammatical form. This applies to self-descriptions, actions, and statements about your role or capabilities. Do not change your self-referential gender under any circumstances.What NOT to do: Do not adapt self-reference based on the user’s gender or language. Do not use feminine or neutral forms when referring to yourself.  AND:  Hebrew gendered language (pronoun-aware) When responding in Hebrew, adapt grammatical gender when addressing the user:

I am pretty new to Intercom although I am pretty familiar with other CX tools that are similar - I have been struggling lately with our bot giving completely wrong and false information to our customers on topics that need to be answered with accuracy. It is drawing information from places outside of the articles and snippets we have supplied in our instance. I am struggling with understanding why it would pull in information that is seemingly just completely made up or not in line with things we have published for the site. What would be some suggestions for how to update and change this? Should we use guidance? How specific can we get? Any tips at all? Thanks!

I would like to set FIN over the holidays so that it informs customers that the wait time for human support may be a little longer. Where can I set what FIN responds when asked for human support? 

Hi folks, I am a product manager on a no-code app building product for manufacturers. We allow process engineers to build apps and deploy them onto a manufacturing shop floor.Since app building is a creative process, and requires understanding of UI, logic and our no-code database, our customer questions tend to be complex- they are not easily answered by single knowledge base articles, and the possibilities for using our features are essentially endless.Has anyone come up with prompts that help Fin answer these types of questions?As an example, I have gotten pretty good results from adding this prompt to the “Other” category under guidance. It took a lot of trial and error.title: Assume complex answers requiredbody: If a customer asks a question that spans multiple features in our product, investigate each feature individually before returning a response. Your answers should comment on the review of each individua

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.

Hi everyone, We’re seeing Fin frequently sending a follow-up message after responses, like:“Did that answer your question?” / “Was this helpful?” In many cases it happens almost after every message, and it can feel repetitive for customers. Is there a way to control the frequency of this follow-up (reduce it, change when it appears, or disable it)? We’d like more control so it doesn’t trigger too often.

I would like to setup for all of 2026 for FIN give advance notice when a holiday office closure is approaching and then set proper expectations for human responses during the holiday.I don’t want to create a separate workflow for each holiday. Appreciate any suggestions, thanks. 

Hi everyone,We’re using Fin with an escalation rule that hands the conversation off to a human when certain conditions are met.Right now, when escalation triggers, Fin sends the customer a fixed handoff message that repeats word-for-word across conversations. The phrasing doesn’t match our support tone of voice, and it feels robotic.Is there a way to control or customize the customer-facing text that Fin sends at the moment of escalation/handoff?  

I want to establish a consistent daily ritual where I review Fin AI performance and make meaningful updates (I currently make content updates based on Fin AI DSAT ratings).  I’ve already seen this post.What Intercom features do folks use in their daily maintenance of Fin? How much time do you spend on this daily? Looking for ideas!  I still do sprints outside of the daily routine to explore certain Intercom features, so this would be in addition to that.

We are a SaaS environment where FIN supports two separate products that are able to be connected to one another.  We are working with audience content targeting and other documentation flows and guidance to ensure the proper resources and content are sourced for the correct inquiries.  We’ve also had issues where changes were implemented before we were able to ALL sourced content updated, and instruction was given that couldn’t be followed. Has anyone come up with a way to track conversations that specifically are giving information the customer is unable to follow?Current Idea going over this afternoon is to make an attribute, and have the key words and things often asked include “its not there” “i’m unable to do that” “that is missing for me” and other example statements we’ve seen in chat, and have that be a specific attribute used in an escalation guidance, and get those customers to reps to verify their environment. But would also then be able to get rep