Multi-Genie Slack Bot: Production-Grade Conversational Analytics in Slack with Databricks Genie Spaces

May 01, 2026

Connect multiple Databricks Genie spaces to Slack with per-user authentication, intelligent routing, semantic caching, and audit logging — all deployed as a Databricks App. A production-grade Slack bot that brings Databricks Genie directly into Slack, allowing users to ask natural-language questions across multiple data domains without leaving their workspace.

Special Thanks

I extend my sincere thanks to Sunil Patil (https://www.linkedin.com/in/pppsunil/) for his invaluable help during the brainstorming phase. His insights were instrumental in solving the complex challenge of managing multiple genies across multiple Slack channels. This project definitely levelled up thanks to his help!

Features

Multi-Genie Support: Route questions to the right Genie space based on channel, thread, AI classification
Per-User Authentication: Use OAuth 2.0 User-to-Machine with PKCE so queries run under each user’s Unity Catalog permissions
Threaded Conversations: Maintain Genie context across Slack threads
Semantic Cache: Reuse answers for similar questions using Databricks Vector Search
Delta-Aware Cache Invalidation: Automatically invalidate cached answers when underlying Delta tables change
Audit Logging: Track user activity, cache hits, latency, errors, and Genie usage in Delta tables
Reliable Genie Calls: Handle rate limits with retry, exponential backoff, and adaptive polling
Native Deployment: Run the entire application as a Databricks App with no external infrastructure

Architecture

The application runs as a Databricks App and uses two services:

Slack Bolt in Socket Mode to listen for messages, mentions, button clicks, and threaded replies
Flask to handle OAuth callbacks and health checks

When a user asks a question in Slack, the bot follows this flow:

1. Checks whether the Slack user has a valid Databricks OBO token

2. Routes the question to the correct Genie space

3. Looks for a semantically similar cached response

4. Validates cached answers against Delta table versions

5. Sends the question to Genie on cache miss

6. Formats the response in Slack with SQL, tables, and suggested follow-ups

7. Writes cache metadata and audit logs to Delta

Prerequisites

1. Databricks workspace

Active Databricks workspace
One or more Genie spaces
SQL Warehouse
Unity Catalog permissions
Vector Search endpoint and index

2. Slack App

Slack workspace with admin access
Slack app with Socket Mode enabled
Bot token and app-level token

3. OAuth App

Databricks OAuth application configured for User-to-Machine authentication
Redirect URI pointing to the Databricks App callback endpoint

4. Download the application code and make the necessary updates to the config values in app.yaml. Download all files from repo: https://github.com/adgitdemo/ad_databricks/tree/main/multi-genie-multi-slack-channel-app

Setup Instructions

1. Slack App Setup

Create a Slack app and enable Socket Mode.
Under OAuth & Permissions, add these bot token scopes:
- app_mentions:read
- chat:write
- im:history
- im:read
- im:write
- channels:history
- groups:history
- users:read
Subscribe to these bot events:
- app_mention
- message.im
- message.channels
- message.groups

Install the app to your workspace and save:
- Bot User OAuth Token
- App-Level Token
- Signing Secret

2. Databricks OAuth Setup

Create a Databricks OAuth application for User-to-Machine authentication.
Configure the redirect URI to point to the Flask callback route exposed by the Databricks App.

The bot uses OAuth 2.0 with PKCE to securely link each Slack user to their Databricks identity. After authentication, the user’s pending question is automatically processed, so they do not need to re-type it.

3. Databricks Workspace Setup

Prepare the required Databricks resources:
- Genie spaces
- SQL Warehouse
- Cache Delta table
- Audit Delta table
- Vector Search endpoint
- Vector Search index
- Catalog and schema permissions

Permission Grants Summary

4. Configure the Application

Update the application configuration with:
- Slack bot token
- Slack app token
- Slack signing secret
- Databricks workspace URL
- OAuth client ID
- OAuth redirect URI
- Genie space mappings
- Default Genie space alias
- SQL Warehouse ID
- Cache table name
- Audit table name
- Vector Search endpoint and index
- Cache similarity threshold
- Optional Service Principal fallback flag

Example routing configuration:

{
“trips-data”: {
“space_id”: “your-trips-genie-space-id”,
“description”: “Questions about trips, pickup locations, fares, and distance”
},
“finance”: {
“space_id”: “your-finance-genie-space-id”,
“description”: “Questions about revenue, spend, forecasts, and financial KPIs”
}
}