An automated framework designed to handle the end-to-end lifecycle of data-driven AI research and development. It utilizes LLM agents to automate data processing, model selection, and iterative optimization processes.
Tech Stack
PythonAI, ML & Data
Why RD-Agent?
• Reduces manual R&D overhead
• Standardizes data-to-model workflows
• Integrates with existing AI stacks
Limitations
• High LLM token cost
• Requires complex initial configuration
• Limited documentation for niche use cases
3/6/2026
Last Update
1,327
Forks
138
Issues
MIT
License
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