AI AGENTS

Recurring Question Mined into a Sourced FAQ Entry

When a recurring question is submitted via chat, the agent researches a verified answer.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerchat
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerQuestion submitted via chat
  • ActionResearch a sourced answerPerplexityPerplexity
  • ActionWrite FAQ answer with confidence ratingOpenAI
  • LogicBranch on confidence for review vs publish
  • ActionUpsert entry into Airtable knowledge baseAirtableAirtable
  • OutputReply with answer and publish status

What it does

Turns repeated incoming questions into a self-building, sourced FAQ. Each new question is researched once, written as a clean answer with citations, and stored in Airtable, so your knowledge base grows from real demand instead of guesswork.

When to use it

Use it when the same questions keep coming up in support, sales, or internal channels and you want a living, sourced knowledge base that stays accurate. Good for teams formalizing tribal knowledge without a full docs project.

How it works

  1. 1A chat-submitted question triggers the workflow with the question text.
  2. 2Perplexity researches a current, sourced answer to the question.
  3. 3OpenAI writes a concise FAQ-style answer, attaches sources, and returns a confidence rating.
  4. 4A logic branch checks confidence: low-confidence answers are tagged for human review instead of auto-publishing.
  5. 5The answer and its sources are upserted into the Airtable knowledge base, matched on the normalized question.
  6. 6The chat reply returns the answer plus a note on whether it was published or queued for review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PerplexitySearch-grounded answers with citations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect AirtableBases, tables, views, automations.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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