AI AGENTS
On-Demand Sourced Brief from Chat into Notion
Ask a question in chat and get a structured, citation-backed research brief written to a new Notion page.
How it runs
The automated pipeline, trigger to output.
- TriggerChat message requesting a brief
- ActionSourced web search on the topicPerplexity
- ActionFetch additional primary sourcesExa
- ActionSynthesize structured brief with citationsOpenAI
- ActionCreate Notion page with the briefNotion
- OutputReply in chat with summary and page link
What it does
Turns a one-line chat request into a polished research brief with inline citations, saved as its own Notion page. You ask "brief me on the EU AI Act enforcement timeline" and get back a structured doc plus a shareable link, no manual searching or copy-paste.
When to use it
Reach for this when a teammate or exec needs a fast, sourced primer on a topic and you want the output to live somewhere durable instead of scrolling away in chat. Good for pre-meeting prep, market questions, and "can someone look into this" asks.
How it works
- 1A chat message starting with a brief request triggers the workflow and passes the question as the topic.
- 2Perplexity runs a sourced search on the topic and returns answers with reference URLs.
- 3Exa fetches additional high-quality primary sources to broaden coverage beyond the first pass.
- 4OpenAI synthesizes both result sets into a structured brief: summary, key findings, and a numbered source list.
- 5A new Notion page is created under the research database with the formatted brief and citations.
- 6The chat reply returns a one-line summary plus the Notion page link.
Set it up
What you configure once, before turning it on.
- 1Connect PerplexitySearch-grounded answers with citations.
- 2Connect ExaNeural search across the web.
- 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 AI Agents workflows
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Datadog Bill Spike Attribution Agent
When a daily Datadog cost check detects a spend jump, an agent attributes the increase to the specific services and metric types driving it and posts a ranked breakdown to Slack.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
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.
