🤝 Build a Slack-based CRM assistant with HubSpot and Google Gemini
⚡ 42 views · 🤝 CRM & Sales Operations
Description
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
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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.
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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.
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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.
- AI Agent – Uses AI to format and structure the CRM data into a readable response.
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
🔗 Nodes Used
Slack, HubSpot, Filter, AI Agent, Google Gemini Chat Model, Slack Trigger
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File