Nimble Web Search Agents

Nimble is a web search layer designed for AI intelligent entities, not for human users. Its main selling point lies in its self-learning capability: the more times the same research task is executed, the more accurate the search strategy in that field becomes. This functionality is achieved through the use of a custom-built index and a memory mechanism.

The product lines are clearly defined: the Agent API is used for automated web research tasks, the Search API retrieves real-time data, and the Extract API extracts structured fields from specified URLs. In addition to direct API calls, integration with MCP Server and mainstream frameworks is also available; systems such as LangChain and Snowflake can all be connected using these methods.

The two key metrics it emphasizes are accuracy and token cost: During retrieval, only the necessary parts of the text are selected, rather than entire pages being fed into the large model for processing. This approach effectively saves on the number of tokens required. Additionally, each search operation generates an auditable Search Plan that details what was searched and why, which is particularly useful in compliance-related scenarios.

It is targeted at developers and teams working on intelligent agent products. Free quotas are available for trial use, but larger-scale applications require further discussion. The company recently announced the completion of a $47 million Series B financing round.