Data Agents Platform
by HotTechStack
Data Agent is an agentic AI harnessing GenAI to automate and streamline data engineering workflows. By delivering complete, well-prepared data requests, it saves time and reduces bottlenecks across teams.
Last updated: N/A
What is Data Agents Platform?
Data Agents Platform is an AI-powered system that uses multiple specialized agents to automate and streamline data engineering workflows. It connects to various backends and integrates with n8n for orchestration, providing a modern UI and easy deployment with Docker.
How to use Data Agents Platform?
To use Data Agents, clone the repository, configure API keys, and use Docker Compose to start the application. Alternatively, you can run it locally. Interact with the agents through the provided interface to automate data engineering tasks.
Key features of Data Agents Platform
Multi-agent collaboration
Multiple backend support (OpenAI, Claude, Gemini, Ollama)
n8n integration
Strategy-based approach
Modern dark UI
Docker ready
Use cases of Data Agents Platform
Designing data infrastructure
Building efficient data pipelines
Analyzing and interpreting complex data
Applying statistical models and machine learning
FAQ from Data Agents Platform
What is a Data Agent?
What is a Data Agent?
A Data Agent is a specialized AI agent designed to automate specific data engineering tasks.
What backends are supported?
What backends are supported?
The platform supports OpenAI, Claude, Gemini, and Ollama.
How do I integrate with n8n?
How do I integrate with n8n?
Upload the workflow from the agents/n8n/conversations directory and configure your API keys in both Docker Compose and the n8n workflow.
Can I run the application locally?
Can I run the application locally?
Yes, you can run the application locally without Docker by installing dependencies and starting the development server.
How can I contribute to the project?
How can I contribute to the project?
Fork the repository, create a new branch, make your changes, commit them, push to the branch, and open a pull request.