Nimble claims its new, domain-specialized Web Search Agents cut token costs in half while boosting retrieval accuracy
Nimble, a New York City-based tech startup VentureBeat previously covered for its efforts to re-invent web search for enterprises by using multiple AI agents to improve accuracy and depth, is taking another step toward its vision of a world in which agents do most of the web searching instead of us typing and reviewing the results manually.
Nimble today launched Web Search Agents, a new retrieval system designed to help AI agents perform more 21% more accurate web research while using significantly fewer tokens — 51% less compared with leading AI search alternatives on comparable, according to the firm.
While Nimble did not disclose its specific benchmarking methodology or competitors evaluated, the results underscore a growing trend in enterprise AI: optimizing retrieval has become as important as improving the underlying language models themselves.
Nimble's leadership says the product combines self-learning retrieval strategies, proprietary web indexes, and live web...
Copyright of this story solely belongs to venturebeat.com. To see the full text click HERE
