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.
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 queriesBrave Search
- ActionAgent synthesizes thesis-impact dossierOpenAI
- OutputPublish dossier to Notion research DBNotion
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
- 1A webhook delivers the flagged filing reference from an upstream watcher.
- 2The agent fetches and reads the filing, then plans its investigation.
- 3The agent issues iterative Brave Search queries to gather corroborating context and history.
- 4The agent synthesizes a thesis-impact dossier with findings, evidence links, and open questions.
- 5The dossier is published as a structured Notion page in the research database.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect Brave SearchWeb, news, image, video search.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect NotionPages, databases, comments.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Market Research workflows
Enrich Inbound Accounts with BigQuery Firmographics and Score Fit
When a new account row lands in Airtable, joins it against BigQuery public business datasets to attach firmographic attributes.
Blend BigQuery TAM with Live Competitor Signals into a Notion Brief
On demand, sizes a chosen segment from BigQuery public data, gathers current competitor signals via Brave Search, and synthesizes a one-page market brief into Notion.
Allocate Sales Territory TAM from BigQuery Geo Data to HubSpot
When triggered by a webhook, queries BigQuery public ZIP-level business data to compute TAM per sales territory.
Hiring Surge Detector with Slack Alert
Detects when a target account's open-role count jumps above its recent baseline and posts a ranked Slack alert to the GTM channel so reps can act on a company that is clearly…
Tech-Stack Shift Inference from Job Descriptions
Reads new job descriptions for target accounts, uses an LLM to extract named technologies and infer stack changes.
Weekly Hiring-Intel Briefing for GTM
An agent reviews the week's accumulated hiring signals across all target accounts, writes a narrative briefing that infers each account's likely initiatives.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.
