Build a Slack-based CRM assistant with HubSpot and Google Gemini

How it works
This workflow creates a Slack-based CRM assistant that allows users to query HubSpot data using natural language. When a user mentions the bot in Slack, the message is cleaned and processed to remove Slack-specific formatting. The workflow then retrieves and filters relevant data from HubSpot (deals, companies, and contacts). Finally, an AI agent formats the response and sends a structured reply back to Slack.

Step-by-step

Trigger on Slack mention**
Slack Trigger – Listens for app mentions in Slack channels.
Code in JavaScript – Cleans the message by removing Slack IDs and formatting.

Fetch and filter CRM data**
Get Deals – Retrieves deals from HubSpot.
Filter Deals – Filters deals based on the user query.
Get many companies – Fetches company records from HubSpot.
Filter Companies – Matches companies against the query.
Get Contacts – Retrieves contact data from HubSpot.
Filter Contacts – Filters contacts using name-based matching.
Merge – Combines filtered deals, companies, and contacts into one dataset.

Generate and send AI response**
AI Agent – Uses AI to format and structure the CRM data into a readable response.
Google Gemini Chat Model – Provides the language model for the AI agent.
Send a message – Sends the final response back to the Slack channel.

Why use this?

Enables instant CRM access directly from Slack without logging into HubSpot
Simplifies data lookup using natural language queries
Combines multiple CRM objects into a single intelligent response
Improves team productivity with faster decision-making
Easily customizable for additional fields, filters, or AI formatting