AI AGENTS
Open Question to Sourced Evidence Table
Takes a research question you submit, runs a multi-source web search, and returns a Notion evidence table where every claim is backed by a cited source and tagged…
How it runs
The automated pipeline, trigger to output.
- TriggerResearcher submits an open question via form
- ActionNeural web search for candidate sourcesExa
- ActionCorroborate top facts with second enginePerplexity
- ActionExtract atomic claims and assign confidence flagsOpenAI
- ActionWrite each claim as a row in the evidence tableNotion
- OutputNotify researcher with link to finished tableSlack
What it does
Turns a single open-ended question into a structured, sourced evidence table. The agent searches the live web, reads the strongest sources, extracts discrete claims, and writes each claim to a Notion database row alongside its source URL, a one-line supporting quote, and a confidence flag (High / Medium / Low) reflecting source quality and corroboration.
When to use it
Use it when you need a defensible answer fast and want to see the evidence, not just a paragraph. Good for market sizing questions, competitive checks, due-diligence prompts, or any decision where "where did this come from?" matters.
How it works
- 1You submit a question through a form trigger.
- 2The agent runs a neural web search to gather candidate sources.
- 3It cross-checks the top hits with a second search engine to corroborate facts.
- 4An LLM extracts atomic claims and assigns each a confidence flag based on agreement across sources.
- 5Each claim is written as a row in a Notion evidence table with source link, quote, and flag.
- 6You get a Slack ping with a link to the finished table.
Set it up
What you configure once, before turning it on.
- 1Connect ExaNeural search across the web.
- 2Connect PerplexitySearch-grounded answers with citations.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect NotionPages, databases, comments.
- 5Connect SlackChannels, DMs, threads, mentions.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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