The Hybrid Search Tool
Blend exact keyword matching with semantic similarity in a single ranked result set so an agent gets both precision and recall — the retrieval default when either alone falls short.
Your answer exists — retrieval just can’t find it
Private knowledge is only useful if an agent can retrieve exactly the right piece and ground its answer in it. Keyword search misses, hosted RAG can’t touch sensitive data, and ungrounded models make things up.
Keyword search misses
The right content is phrased differently than the query.
Ungrounded answers
Without retrieval, models invent instead of cite.
Scale hides signal
The best chunk is buried among thousands of near-matches.
Hosted RAG is off-limits
Sensitive knowledge can’t go to a third-party index.
Hybrid Search, without the risk
Capability
What it does
Combine keyword and semantic search for the best of both.
it runs keyword and semantic search together and fuses them into one ranked result set.
Assignable to any agent
How it works
Predictable, inspectable behavior
Designed to be reliable.
it merges lexical and vector scores with a tunable weighting, so exact-term precision and meaning-based recall reinforce each other instead of competing.
Every call logged
Governance
Private, governed, on-premise
Runs inside your perimeter.
Indexing and retrieval run on-premise or in your sovereign cloud, scoped per tenant and audit-logged, so even sensitive knowledge is searchable and citable without any of it leaving your perimeter.
Per-tenant, logged
Parameters
The hybrid_search tool accepts these inputs when an agent calls it. Required inputs are flagged.
default: 10 Optional Maximum results to return (1–50).
default: 0.5 Optional Weighting between keyword (0) and semantic (1).
How the Hybrid Search tool works in practice
Hybrid Search is a semantic search & rag tool you assign to a VDF AI agent. It runs keyword and semantic search together and fuses them into one ranked result set. Its hallmarks — Hybrid, Keyword+Vector, Fused — let an agent rely on it as a dependable step in a larger task rather than a brittle one-off script.
Under the hood, it merges lexical and vector scores with a tunable weighting, so exact-term precision and meaning-based recall reinforce each other instead of competing. It expects query and user_id as required inputs, so calls are explicit and easy to audit. Every call is scoped to the requesting tenant and written to an audit log, so the capability is safe to run inside a regulated, on-premise environment — the same governance model behind every VDF AI tool.
Teams reach for Hybrid Search when they need to handle best-of-both recall, codes and names, and robust RAG. It rarely works alone — pair it with Result Reranker, RAG Vector Query, and ALL Vectors Search to build a complete, governed workflow, then compose those steps into an on-premise VDF AI Network.
Where Hybrid Search pays back
Best-of-both recall
Catch exact terms and paraphrases in one query.
Codes and names
Match SKUs or IDs precisely while still ranking by meaning.
Robust RAG
Reduce misses that pure semantic search makes.
Tunable
Bias toward exactness or meaning per use case.
Assigned to agents, orchestrated as networks
On VDF AI, an industry’s use cases map to agents, and you assign tools like this one to those agents. Compose multiple agents into a governed, on-premise network.
What changes after you assign it
Questions about the Hybrid Search tool
What is the Hybrid Search tool?
It runs keyword and semantic search together and fuses them into one ranked result set. Assigned to a VDF AI agent, it runs under role-based policy with full audit logging so the capability is safe to use in production.
When does hybrid beat pure semantic search?
When queries mix exact identifiers (codes, names) with natural language — hybrid catches both.
Can I control the balance?
Yes. The alpha parameter weights keyword vs semantic scoring.
What inputs does the Hybrid Search tool need?
It requires query and user_id, and optionally accepts top_k and alpha. Each parameter is validated when an agent calls the tool, and the full call is logged for audit.
Which tools pair well with Hybrid Search?
Hybrid Search is commonly assigned alongside Result Reranker, RAG Vector Query, and ALL Vectors Search. On VDF AI you compose several tools and agents into a single governed, on-premise network.
Does it run on-premise?
Yes. Like every VDF AI tool, it can run on-premise or in your sovereign cloud, scoped per user and audit-logged, so your data never leaves your perimeter.
How do agents use it?
You assign the tool to an agent under a role-based policy; the agent calls it as one step in a task, and several agents and tools can be orchestrated together as a governed VDF AI Network.
Assign Hybrid Search to these agents
These VDF AI agents can be assigned this tool. Open an agent to see the full toolkit it can run.
Tools that work well alongside this one
Where this tool delivers value
Put Hybrid Search to work
See the Hybrid Search tool assigned to an agent and orchestrated in a governed, on-premise network.