Mistral AI introduced Search Toolkit in public preview as a composable framework for AI search infrastructure. It unifies ingestion, retrieval, and evaluation with support for parsing, chunking, embeddings, BM25, dense retrieval, hybrid search, and standard retrieval metrics. The toolkit targets enterprise search, RAG quality improvement, and domain-specific retrieval, with a starter app using Docker, uv, and Vespa.
Google Research and Google Cloud introduced an agentic RAG framework hosted on Gemini Enterprise Agent Platform. It uses multiple agents to plan, rewrite, route, retrieve, verify sufficient context, iterate, and synthesize answers. Google reports up to 34% factuality accuracy gains over standard RAG, plus 90.1% accuracy in a cross-corpus FramesQA setting with similar latency to single-corpus retrieval.