Support

Fin AI Self-Learning FAQ

An AI agent trained on your knowledge base resolves 40%+ of support tickets and learns from every new human answer.

The problem
Every support agent answers the same FAQ 50 times a day. Your knowledge base exists but no one searches it. New repeat questions never get added — so the cycle never breaks.
  • 40% load reduction on day-1 deployment baseline
  • 150+ typical Q&A pairs cover most of inbound volume
  • Self-learning loop: KB grows ~10-20 articles/month with zero manual upkeep
Our solution

Intercom Fin AI loaded with your full knowledge base (~150 typical Q&A). When a novel repeated question appears, Fin watches the human's answer, summarizes it, proposes a new KB article, and starts answering it next time. KB grows automatically.

How it works
  1. 01
    KB ingestion
    Existing help center, FAQ docs, internal wikis, and Notion pages imported into Intercom. Fin chunks and embeds them.
  2. 02
    Custom guardrails
    Brand voice, prohibited topics, escalation triggers (refund, complaint, B2B inquiry) configured per your playbook.
  3. 03
    Live answering
    Fin AI replies to every inbound question. Cites sources. Handles follow-ups in conversation. Escalates when confidence drops.
  4. 04
    Self-learning loop
    When Fin escalates and a human answers, Fin proposes a new KB article. Admin reviews + approves in one click — Fin starts answering it next time.
  5. 05
    Hand-off with context
    On escalation, Make.com summarizes the conversation via GPT-4 and pushes a structured Deal into Pipedrive (for sales-relevant questions).
  6. 06
    Performance dashboard
    Weekly report: % resolved by Fin, top unresolved questions, KB articles added, CSAT split (Fin vs human).
Tools we use
Intercom Fin AIMake.comOpenAI GPT-4PipedriveNotion
Expected outcomes
  • 40%+ tickets resolved by Fin on day 1, scaling toward 60-70%
  • KB grows 10-20 articles/month without manual upkeep
  • Support team reallocated from FAQ to high-value escalations
  • CSAT on Fin-resolved tickets matches or beats human (instant + accurate)
Best for

Support teams handling 200+ tickets/day with an existing knowledge base — SaaS, eCommerce, fintech, marketplaces.

Pricing tier
Enterprise
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