Industrial AI Agent System: Mid-term Progress and Technical Achievements
Date:
Mid-term progress report for the Rootcloud AI Agentic System R&D project (¥400,000 funding). Presented achievements in developing end-to-end agentic AI system with integrated RAG, reinforcement learning, and multimodal understanding. Demonstrated: (1) Agentic RAG prototype achieving 60%+ retrieval recall and answer accuracy; (2) RL-optimized agent models with 5%+ improvement over baselines; (3) Multimodal context management reducing token usage by 50% while maintaining 80%+ accuracy. Showcased industrial applications in autonomous fault diagnosis, dynamic tool invocation, and multi-turn reasoning. Outlined remaining work including production deployment, scalability testing, and integration with enterprise systems.