AI AGENTS

Evidence-Backed Research Pack from a Submitted Topic

Submit a research question via webhook and an agent gathers primary sources, extracts supporting evidence with citations.

CategoryAI Agents
Enginesim
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook receives questionHTTP webhook
  • ActionSearch candidate sourcesExa
  • ActionScrape sources to textFirecrawl
  • ActionExtract cited findingsOpenAI
  • ActionSave research pack to DriveGoogle DriveGoogle Drive
  • OutputReturn findings as JSONHTTP webhook

What it does

Given a research question posted to a webhook, this agent compiles an evidence pack: the question restated, a synthesized answer, and a list of findings where each is tied to a quoted passage from a real source it fetched. Output goes to a stored document and a structured JSON response for downstream tools.

When to use it

For teams building research into a larger workflow — an internal tool, a knowledge base ingest, or an RFP-response pipeline — that need machine-readable findings with citations, not just prose.

How it works

  1. 1An HTTP webhook receives the research question and parameters.
  2. 2Exa runs targeted neural search and returns ranked candidate sources.
  3. 3Firecrawl scrapes each candidate to clean text for grounded reading.
  4. 4The agent (OpenAI) extracts discrete findings, each with a verbatim supporting quote and source URL, and writes a synthesized answer.
  5. 5The structured findings are saved as a document in Google Drive for the record.
  6. 6The webhook returns the same findings as JSON so the calling system can consume them.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect ExaNeural search across the web.
  3. 3
    Connect FirecrawlCrawl, scrape, structured extract.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Connect Google DriveDocs, sheets, slides, files.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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