Nimble launches Web Search Agents to cut AI research token costs
Web search platform company Nimble today launched Web Search Agents, a product that learns a customer’s domain and then runs complex web research tasks on its own.
The company is aiming the release at teams that have found general-purpose web search too blunt for production agents. Generic tools return a wide, unstructured set of results and leave the agent to work out what is actually relevant, an approach that burns tokens on unnecessary tool calls and on processing pages that do not matter.
Nimble’s pitch is that a market research agent and a lead enrichment agent should not get the same product. Its harness self-learns the knowledge work involved in a task and adapts retrieval strategies to it, combining proprietary indexes with real-time retrieval from live sites to pull what the company describes as the freshest and most granular information available.
Benchmark testing published by Nimble showed a 21-point increase in answer quality and 51% fewer tokens spent per query.
