@jerryjliu0: We've created a comprehensive Retrieval Harness for modern agentic retrieval in 2026. The harness provides a persistent…
Summary
LlamaIndex has created a Retrieval Harness for modern agentic retrieval, providing a persistent data pipeline for connecting, indexing, and querying large knowledge bases with tools like semantic search and regex grep, allowing agents to autonomously navigate knowledge bases.
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Cached at: 07/04/26, 02:48 PM
We’ve created a comprehensive Retrieval Harness for modern agentic retrieval in 2026.
The harness provides a persistent data pipeline that can connect to a data source, index and update a large knowledge base, and expose a broad set of tools akin to filesystem operations (semantic/keyword search, regex grep, file search, read).
You can plug this into any of your agents to let them autonomously crawl an arbitrary knowledge base to solve a task with any complexity.
Check out our reference implementation: https://github.com/run-llama/legal-kb…
LlamaParse: https://cloud.llamaindex.ai
LlamaIndex 🦙 (@llama_index): Agentic retrieval is changing the way retrieval-augmented applications are built, especially in domains like legal and fintech, where agents need to autonomously navigate large, evolving knowledge bases.
That’s exactly the use case we designed Index v2 for.
To demonstrate
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