What Nimble is

Nimble is web search and retrieval for AI agents. It discovers and captures the most complete, accurate web context for what an agent is trying to do, then returns it as cited, structured output the agent can use directly.

Connecting an agent to the web is easy. The hard part is getting the context the agent actually needs. Generic search uses the same index and retrieval logic for every agent, so results come back incomplete, irrelevant, or untrusted. Nimble is built to close that gap.

How Nimble is different

• Self-learning retrieval, specialized to your domain. Nimble learns an agent's vocabulary, authoritative sources, success criteria, and output schema. It also remembers which retrieval paths found the right data, so repeat workflows get more accurate and cheaper with every run.

• Computer use for what search results miss. Nimble doesn't stop at a search index. It browses sites directly, rendering JavaScript and clicking through subpages, filters, and pagination, to capture content that never ranks in search.

• Governed, inspectable output. Citations, confidence signals, source controls, and schema enforcement make every result auditable and production-ready.

What Nimble delivers

Nimble offers two ways to use the same retrieval stack:

• Web Search Agents are the managed research layer. Send a task in plain language, optionally with a JSON schema. Nimble plans the work, searches and browses the live web, reasons over what it finds, and returns a cited answer or a structured dataset. Supported modes are research, enrichment, and dataset building.

• Search and Extract APIs are the fast, cost-efficient web data layer for agents that do their own reasoning. Search returns real-time results and page content. Extract and Extraction Templates return clean content or typed fields from known pages.

Core jobs-to-be-done

• Give AI agents and LLM apps real-time web search and grounding

• Delegate multi-step web research to an agent and get back cited, schema-matched answers

• Enrich records such as companies, products, and people with verified web data

• Build structured datasets from the live web, including content behind filters, pagination, and JS-heavy pages

• Power repeat research workflows that improve over time, such as GTM, company research, market analysis, and social monitoring

Who Nimble serves

• AI engineers and agent builders who need complete, accurate web context for their agents

• AI and platform team leaders who want to get trustworthy agents into production without owning retrieval plumbing

• Data, analytics, and research teams in retail and CPG, finance and consulting, and marketing and brand, who use web search agents for research, enrichment, and dataset building

Company facts supported by owned materials

• Nimble says it is building the Web Search Agent Platform.

• A February 24, 2026 company announcement says Nimble was founded in 2022.

• The same announcement says Nimble raised a $47M Series B led by Norwest, and that Databricks joined as an investor.

• The About page shows investors including Norwest, Databricks, Hetz Ventures, Slow Ventures, Square Peg, and Target Global.

• Site footer materials list the address 104 West 27th Street, New York, NY 10001, USA.

• The Careers page lists hiring locations in New York and Tel Aviv.

Mission

Nimble's mission is to give AI agents the complete, accurate, and trustworthy web context they need to act. That means making the live web searchable, verifiable, and usable for every agent.