Integration Tutorial April 13, 2026

Turn Slack Channels into Searchable Knowledge

Decisions happen in Slack -- architecture debates in #engineering, customer feedback in #product, incident responses in #ops-alerts. But Slack's search is keyword-only and history disappears on free plans. REM Labs captures channel conversations as persistent, semantically searchable AI memory.

What Gets Synced

The Slack integration captures messages with their full context:

Channel messages -- every message in selected channels, with author, timestamp, and reactions
Threads -- thread replies are grouped with their parent message as a single coherent conversation
Shared files -- text extracted from files shared in channels (documents, code snippets, images with OCR)
Bookmarked messages -- messages saved with bookmarks are tagged as high-signal content
Channel metadata -- channel name, purpose, and topic stored for namespace scoping

Install the Slack App

In the REM Labs Console, go to Integrations and click Connect Slack. Install the REM Labs Slack app to your workspace and select which channels to sync. The app requires only read access to channel messages.

Import via API

curl -X POST https://api.remlabs.ai/v1/memory/sync/slack/import \
  -H "Authorization: Bearer sk-slop-..." \
  -H "Content-Type: application/json" \
  -d '{
  "slack_token": "xoxb-...",
  "channels": ["C01ABCDEF", "C02GHIJKL"],
  "include_threads": true,
  "include_files": true,
  "oldest": "2025-01-01T00:00:00Z",
  "sync_mode": "incremental"
}'

The oldest parameter sets a start date for the import. This is useful for skipping years of old messages and focusing on recent, relevant conversations. Incremental mode uses message timestamps to only fetch new messages since the last sync.

Thread Grouping

Individual Slack messages are often too short to be useful on their own. The integration groups thread replies with their parent message into a single memory, preserving the full conversation. A thread about "should we use Redis or Memcached for session storage" becomes one searchable memory with the entire decision-making context.

Search Team Knowledge

curl -X POST https://api.remlabs.ai/v1/integrations/slack/search \
  -H "Authorization: Bearer sk-slop-..." \
  -H "Content-Type: application/json" \
  -d '{
  "query": "why did we choose PostgreSQL over DynamoDB",
  "filters": {"channel": "engineering"},
  "limit": 10
}'

This finds the #engineering thread where your team debated database options and the follow-up thread about migration benchmarks -- decisions that were made in Slack and would otherwise be lost to scroll history.

Real-Time Sync

With the Slack app installed, new messages are synced automatically via Slack Events API. Every message posted to a monitored channel is indexed within seconds. No manual re-sync needed.

API Endpoints Reference

Endpoint	Method	Description
`/v1/memory/sync/slack/import`	POST	Import messages from Slack channels
`/v1/integrations/slack/channels`	GET	List available channels for sync
`/v1/integrations/slack/status`	GET	Check sync status and message counts
`/v1/integrations/slack/search`	POST	Search within the Slack namespace

DM privacy: The integration only syncs public and private channels that the Slack app has been explicitly invited to. Direct messages are never accessed. Channel selection is granular -- you choose exactly which channels to monitor. See Slack integration docs.

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