MARKET RESEARCH

Agent-Driven Deep-Dive Filing Investigation to Notion

When a flagged filing arrives, an agent autonomously researches it across multiple sources, pulls supporting context, builds a thesis-impact write-up.

CategoryMarket Research
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook delivers flagged filingHTTP webhook
  • ActionAgent fetches and reads filingOpenAI
  • ActionAgent runs iterative Brave Search context queriesBraveBrave Search
  • ActionAgent synthesizes thesis-impact dossierOpenAI
  • OutputPublish dossier to Notion research DBNotionNotion

What it does

This workflow hands a flagged filing to an autonomous research agent that decides what to investigate. The agent reads the filing, runs follow-up Brave Search queries to corroborate or contextualize the change, pulls related prior disclosures and news, and assembles a thesis-impact dossier covering what changed, why it matters, and open questions. The dossier is published to Notion.

When to use it

Use it when a single filing warrants real investigation rather than a one-line summary, for example a surprise guidance cut or a novel risk factor you want fully contextualized before the morning meeting. It is for depth, not speed.

How it works

  1. 1A webhook delivers the flagged filing reference from an upstream watcher.
  2. 2The agent fetches and reads the filing, then plans its investigation.
  3. 3The agent issues iterative Brave Search queries to gather corroborating context and history.
  4. 4The agent synthesizes a thesis-impact dossier with findings, evidence links, and open questions.
  5. 5The dossier is published as a structured Notion page in the research database.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect Brave SearchWeb, news, image, video search.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect NotionPages, databases, comments.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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