Self-learning domain research
Agents accumulate web context over time and adapt to a specific research domain, helping them handle recurring tasks without requiring a new methodology for every request.
Nimble Web Search Agents are self-learning research agents that search and crawl the live web for domain-specific answers, enrichment, and structured datasets. They are designed for teams building repeatable research workflows where the schema, search scope, and output format need to be controlled.
Nimble Web Search Agents automate domain-specific web research by combining live web search, web crawling, and structured data extraction. They can access current webpages and relevant subpages, follow a defined research plan, and return answers, enrichments, or datasets.
Users define the fields or schema they need, allowing results to remain consistent across repeated runs. The agents adapt to the selected domain and research task, accumulate web context over time, and work within the scope and guardrails of the search plan. This makes the product suitable for recurring research and enrichment workflows rather than one-off generic searches.
Agents accumulate web context over time and adapt to a specific research domain, helping them handle recurring tasks without requiring a new methodology for every request.
Define the fields and structure required for a workflow so results can be returned consistently as answers, enrichments, or datasets.
Combine web search with domain crawling to reach relevant pages and subpages, including sources that may not be fully represented in conventional search indexes.
Set the scope and guardrails for the research plan, giving builders control over what the agent should retrieve and how narrowly it should focus.
The beta monitoring capability is designed to continuously track a selected data point on a webpage in real time.
Use Nimble’s Agent API to automate search, crawling, research, enrichment, and dataset-creation workflows; related platform tools include extraction, crawling, and URL mapping.
Build repeatable workflows for company reports, discovery, and enrichment by collecting targeted information from live web sources.
Track products, pricing, assortment gaps, and other market signals to support competitive research and digital-shelf analysis.
Create research datasets for finance workflows, including comparing analyst earnings predictions with actual outcomes.
Identify businesses that match an ideal customer profile and enrich company or dependency records with relevant health indicators.
Use the monitoring capability to follow a specified data point on a webpage, such as a market, social, travel, or product signal that may change over time.
Depending on the workflow, agents can return research answers, structured enrichments, or datasets. Users can define a schema to keep the returned fields consistent across runs.
Yes. Nimble describes Web Search Agents as combining web search with domain crawling so they can access relevant subpages and retrieve information from specific domains.
Builders can define the schema and set the scope and guardrails for the search plan. Nimble also provides related APIs for search, extraction, crawling, and URL mapping.
Supported examples include company research, due diligence, market analysis, real estate, social media monitoring, travel and hospitality, finance, product intelligence, and GTM research.
Nimble presents a free starting option and a Start Free flow. Paid platform plans are also available, with plan differences including agent concurrency, monthly web-page credits, data storage, and custom workflow capabilities.
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