Chat to DB: Natural language SQL queries via AI
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Uploaded: 12.01.2026
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# Chat-based analytics for MySQL: natural language queries with AI and chat memory
This automation enables users to ask questions in natural language via chat, which are converted into accurate SQL queries to MySQL using a LangChain AI agent powered by Groq. Results are returned directly in the chat interface—no coding or direct database access required. Ideal for real-time analytics and secure, self-service data access.
## Who it´s for
- Analysts who need quick data access without writing SQL manually.
- Managers requesting customer, order, or debt information without technical skills.
- Developers testing AI-generated SQL and validating query logic.
- Teams aiming to empower non-technical staff with conversational data access.
## What the automation does
- Receives a text message from a chat as an input query.
- Routes the query to a LangChain AI agent (powered by Groq) with knowledge of the MySQL schema and conversation history.
- Generates and executes a safe SQL query against your database.
- Formats results and sends the response back to the user in chat.
- Handles complex queries with JOINs, filters, and aggregations (e.g., ´Show customers from Moscow with debt over 10000´).
## What´s included
- Ready-to-use n8n workflow.
- Trigger logic for chat_message events.
- Integrations with MySQL and Groq API.
- Preconfigured AI agent template with DB schema access and chat memory.
- Basic setup and adaptation guide.
## Requirements for setup
- Access to an n8n instance (cloud or self-hosted).
- Active Groq API account with available credits.
- MySQL server accessible over the network and valid credentials.
- Database schema that will be shared with the AI agent.
## Benefits and outcomes
- Accelerates data retrieval — responses in seconds instead of hours.
- Reduces workload on IT and analytics teams.
- Enables secure data access without granting direct SQL permissions.
- Maintains conversation context: the agent remembers prior interactions.
- Minimizes query errors through model training and schema awareness.
## Important: template only
Important: you are purchasing a ready-made automation workflow template only. Rollout into your infrastructure, connecting specific accounts and services, 1:1 setup help, custom adjustments for non-standard stacks and any consulting support are provided as a separate paid service at an individual rate. To discuss custom work or 1:1 help, contact via chat
This automation enables users to ask questions in natural language via chat, which are converted into accurate SQL queries to MySQL using a LangChain AI agent powered by Groq. Results are returned directly in the chat interface—no coding or direct database access required. Ideal for real-time analytics and secure, self-service data access.
## Who it´s for
- Analysts who need quick data access without writing SQL manually.
- Managers requesting customer, order, or debt information without technical skills.
- Developers testing AI-generated SQL and validating query logic.
- Teams aiming to empower non-technical staff with conversational data access.
## What the automation does
- Receives a text message from a chat as an input query.
- Routes the query to a LangChain AI agent (powered by Groq) with knowledge of the MySQL schema and conversation history.
- Generates and executes a safe SQL query against your database.
- Formats results and sends the response back to the user in chat.
- Handles complex queries with JOINs, filters, and aggregations (e.g., ´Show customers from Moscow with debt over 10000´).
## What´s included
- Ready-to-use n8n workflow.
- Trigger logic for chat_message events.
- Integrations with MySQL and Groq API.
- Preconfigured AI agent template with DB schema access and chat memory.
- Basic setup and adaptation guide.
## Requirements for setup
- Access to an n8n instance (cloud or self-hosted).
- Active Groq API account with available credits.
- MySQL server accessible over the network and valid credentials.
- Database schema that will be shared with the AI agent.
## Benefits and outcomes
- Accelerates data retrieval — responses in seconds instead of hours.
- Reduces workload on IT and analytics teams.
- Enables secure data access without granting direct SQL permissions.
- Maintains conversation context: the agent remembers prior interactions.
- Minimizes query errors through model training and schema awareness.
## Important: template only
Important: you are purchasing a ready-made automation workflow template only. Rollout into your infrastructure, connecting specific accounts and services, 1:1 setup help, custom adjustments for non-standard stacks and any consulting support are provided as a separate paid service at an individual rate. To discuss custom work or 1:1 help, contact via chat
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