Announcing MCP Toolbox Java SDK v1.0: Agentic data access for the enterprise
cloud.google.com·6d ago
Cloud & Infrastructure
The New Stack·Sep 5·5 min read
Building trust in agentic RAG starts with evidence
TL;DR
Agentic retrieval-augmented generation (RAG) enhances user trust by prioritizing evidence-based responses. This approach ensures that generated content is grounded in verifiable information.
✦ Why It Matters
Implement evidence-based practices in your AI systems to enhance user trust and reliability.
Key Takeaways
- Implement structured logging for all retrieval decisions.
- Ensure users receive clear citations with context.
- Document rejected sources and reasons for transparency.
- Establish enforceable retrieval policies for data access.
How It Works
Agentic RAG allows systems to rewrite user queries and select from various data sources, applying different search techniques like lexical and semantic searches. Each decision in this process is logged, creating a detailed evidence trail that enhances trust and accountability.