Nimble Launches Specialized AI Agents for Web Search
Technology firm Nimble has launched new Web Search Agents, which it claims cut token costs in half while boosting retrieval accuracy for enterprise use.
New York-based technology firm Nimble has introduced its new Web Search Agents system, designed to enhance web searches performed by AI agents.
The company states that its new specialized agents can execute web searches with 21% greater accuracy while using 51% fewer tokens compared to competing solutions. Nimble did not disclose its specific benchmarking methodology or the competitors evaluated.
Nimble CEO Uri Knorovich explained that the system utilizes self-learning retrieval strategies, proprietary web indexes, and live web access. "Our research team built self-learning retrieval algorithms that learn a customer's domain," Knorovich stated. "They find the exact information more efficiently, reduce the amount of multi-hop reasoning required, and lower token usage while improving accuracy."
Nimble is targeting developers building autonomous agents that require continuously updated information from the public web for research, lead generation, and competitive intelligence. The system is designed to integrate seamlessly into existing enterprise systems via an API.
The company aims to differentiate itself from general-purpose search engines by offering specialized solutions. Nimble's long-term vision is for each enterprise to have its own methods for searching, retrieving, and validating external information, acknowledging that different businesses have distinct preferences for data sources and trust standards.