The most important decisions your team makes rarely end up in formal documentation. Half of them live in a Slack thread. The other half are in a Notion page only three people know about.
In this video, Brandon will show you how to ingest data directly from Slack and Notion into Cognee, building a single knowledge graph that connects conversations, incident reports, architecture decisions, and sprint retros — across both platforms.
🔗 What we cover:
00:00 Why Slack + Notion matter for your knowledge graph
00:38 The scenario: a new dev investigating an incident
01:25 Walking through the source data in Slack and Notion
02:25 Creating a Slack app and bot ("Cognibot")
02:50 Setting Slack OAuth scopes (read-only: channels:history, channels:read, users:read)
03:36 Installing the bot and grabbing the OAuth token
03:42 ⚠️ Don't forget to invite the bot to each channel
04:09 Creating a Notion integration and access token
04:36 Granting Notion access to your team's pages
04:52 Setting up the Python project with uv
05:09 Configuring .env (Slack, Notion, OpenAI keys)
05:41 Walking through ingest.py — fetching Slack channels
06:06 Fetching Notion pages (titles, blocks, text)
07:07 The main function: one line — cognee.remember()
07:58 Running the ingestion
08:21 Querying across Slack + Notion with cognee.recall()
08:50 The answer: pulled from 6 sources across 2 platforms
09:07 Recap
🛠️ Tools used:
Cognee
Slack SDK (slack_sdk)
Notion Client (notion-client)
Python 3.12 + uv
OpenAI API
▶️ Watch the rest of the series first:
Part 1 — Building a knowledge graph with the Cognee SDK: • Build a Company Brain in Python with Just ...
Part 2 — Sharing your knowledge graph with Cognee Cloud: • Share Your Company Brain with the Whole Te...
Part 3 — Running Cognee on AWS Bedrock: • Connect Cognee to AWS Bedrock — Keep Your ...
Two lines of code (cognee.remember() + cognee.recall()) and a knowledge graph that finally connects the conversations, decisions, and documents scattered across your team's tools.
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