A study from XJTU, SJTU, and ZJU shows RAW-RAG — a simple dense retrieval + reranking pipeline on raw dialogue history — outperforms 12 agentic memory systems across four benchmarks, achieving higher accuracy with 83× faster ingestion because raw evidence preserves reasoning paths that compression loses.
The OpenViking Gateway sits between AI clients and model services, automatically retrieving and saving conversation memories so clients like Claude Code, Codex CLI, and Cherry Studio gain persistent memory without plugins—just change Base URL and API Key. It supports local or hosted deployment, provides a Studio UI for configuration, and handles multi-step tool calls transparently.
The article explains how OpenClaw tackles the bottleneck of information overload in enterprise research by replacing static keyword search with an Agentic Search loop that iteratively understands, plans, executes, and learns, while Agentic Memory captures and reuses findings across sessions, creating a self‑reinforcing research flywheel.
