LlamaIndex launches hybrid retrieval for LlamaParse, letting AI agents combine semantic search with traditional grep and BM25

Vector databases or pure grep? Teams are split on the right retrieval architecture for agents.
⁣ ⁣ The reality? You need both. Semantic search for a fast first pass; grep and file reads for surgical precision when top-k chunks cut off mid-answer.
⁣ ⁣ On June 29, our Head of Engineering George He goes under the hood on the architecture decisions and dead ends behind building this harness into LlamaParse Index.⁣ ⁣ 
Register here : https://landing.llamaindex.ai/retrieval-harness

Agentic search has moved from fixed RAG pipelines into flexible agent harnesses with access to a set of search tools: keyword search (bm25, grep regex) and semantic search.

When you upload a collection of unstructured documents to LlamaParse, we expose all these tools for agents to access.

Come check out our webinar on June 30th where we explore all these different tools and identify which ones work the best for agentic search:

https://landing.llamaindex.ai/retrieval-harness