Knowledge retrieval is becoming computational infrastructure.

RetrievalRuntime describes the operational machinery that executes retrieval while AI is working. Instead of treating RAG as one static lookup, modern agentic systems can plan searches, retrieve from multiple sources, evaluate evidence, reformulate queries, rerank results, retrieve again, verify coverage, and only then assemble the context required for reasoning. :contentReference[oaicite:0]{index=0}

Query Intelligence

Interpret intent, rewrite queries, decompose complex requests, select retrieval strategies, identify sources, and create parallel retrieval tasks.

Retrieval Operators

Run embeddings, vector search, lexical search, graph traversal, memory access, database queries, APIs, reranking, filtering, and hybrid retrieval.

Agentic Retrieval

Inspect partial evidence, detect information gaps, generate follow-up searches, branch across sources, retry weak retrievals, and terminate when context is sufficient.

Context Assembly

Score, rerank, deduplicate, compress, authorize, verify, cite, and package retrieved evidence into runtime-ready context for models and agents.