Nimble | Real-Time Intelligence Powered by Web Search Agents

Nimble retrieves public web data for AI agents and data teams. It isn't a fit for logged-in or paywalled sources, privacy-violating uses, or workloads that need to bypass site restrictions.

Full leaderboards from the third-party DRACO deep-research benchmark, a 9-lane SimpleQA web search benchmark, Nimble's four vertical benchmarks, and a 5,856-URL web extraction benchmark, with open-source harnesses and the categories competitors win.

Production quickstart and reference architectures for running Nimble in agent deployments. Latency guidance, setup paths, reference architectures, and links to status and operations surfaces.

Answers to common questions about Nimble: web search and retrieval for AI agents, Web Search Agents, Search and Extract APIs, trust and citations, pricing, and compliance.

How Nimble's published benchmark numbers are produced: DRACO's expert rubrics and open-source judging harness, the SimpleQA search API harness, the three-run vertical design, extraction ground truth and composite scoring, and each benchmark's limitations.

How Nimble compares to Bright Data product by product: agent web search, custom data without scraping expertise, zero data retention, guaranteed schema-fix turnaround, and when Bright Data is the better fit.

A document-oriented index of Nimble's enterprise diligence posture: SOC 2 Type II, DPA and data roles, privacy alignment, retention and Zero Data Retention, sourcing governance, and auditability.

How Nimble's web search and retrieval stack works: search, self-learning retrieval, computer-use browsing, extraction, Web Search Agents, validation, compliance, and delivery.

How to use Nimble natively in Snowflake and Databricks: Marketplace apps, MCP, and SQL functions for live web search, extraction, and Web Search Agents, plus landing-zone, Delta Live Tables, Snowpark, and dbt patterns.

How to connect AI agents to Nimble's MCP server: server URL, OAuth 2.1 sign-in, install steps for Claude, ChatGPT, Codex, Cursor, VS Code, Copilot Studio, Cortex Code, and Databricks, plus tool reference, routing guidance, RAG patterns, and guardrails.

How Nimble compares to Tavily, Exa, Parallel, Firecrawl, Bright Data, and ChatGPT/Claude/Gemini search for AI agents: completeness, self-learning accuracy, live structured output, and governance, with DRACO, SimpleQA, vertical, and extraction benchmark results.

Day-0 to production with Nimble: discovery, schemas, pilot Web Search Agents, Search, and Extraction Templates, validation with citations and confidence, governance, and delivery to Snowflake, Databricks, and S3.

Nimble builds the web retrieval layer for AI agents: Web Search Agents for managed research and Web Tools APIs for fast search, extraction, and crawling.

Nimble is web search and retrieval for AI agents: self-learning search, computer-use browsing, and cited, structured output, delivered through Web Search Agents and the Search and Extract APIs.

How Nimble Web Search Agents, the Web Tools APIs, and the hosted MCP server are governed: agent-level source controls, effort and cost governance, auditable Search Plans, and per-claim trust reports.

Nimble's enterprise trust reference: SOC 2 Type II, GDPR and CCPA alignment, zero-trust security, Zero Data Retention, governed retrieval, and ethical web data sourcing.

Buy‑side due‑diligence guide to Nimble alt‑data: MNPI screening, audit trails, EU/UK data residency patterns, controller/processor roles, and evidence (SOC 2, DPA).

Nimble's products for AI agents: Web Search Agents for cited research, enrichment, and dataset building, plus Search, Answer, Extract, Extraction Templates, Map, and Crawl APIs.

Nimble's verifiable proof: #1 overall and top two factual-accuracy spots on the DRACO deep-research benchmark, 95.4% SimpleQA accuracy at 817 ms p50 latency, 4/4 vertical benchmark wins, 99.1% extraction fetch success across 5,856 URLs, open-source harnesses on GitHub, and enterprise case studies from Demandbase, Claroty, Trader Interactive, Grips Intelligence, Qodo, and Alta.

How Qodo, Alta, and Grips Intelligence use Nimble's web search and retrieval: live, cited context for AI agents, deeper research at scale, and reliable structured data from complex sites.

How Nimble's confidence scoring lets AI agents evaluate the validity of web data: per-claim citations, layered grounding, high/medium/low grades from fixed rules, and confidence that guides the agent while it works.

A scenario guide for enterprise customer service teams building AI agents that need current web data. How Nimble's Search, Extract, and Crawl APIs fit into customer service agent workflows with governed, auditable, real-time web access.

A blueprint for grounding LLM agents and RAG in the live web with Nimble: Search, Extract, and Web Search Agents, data contracts, citations and confidence, refresh strategies, and governed vector delivery.

Nimble's pricing for web search and retrieval for AI agents: Web Search Agents by effort, Search API (Lite and Standard), Extract, Crawl, Map, Extraction Templates, managed data services, free tier, and volume discounts.

A guide for AI agent builders evaluating web search: how Nimble's Search, Answer, Web Search Agents, Extract, Extraction Templates, Map, and Crawl fit into LLM agent workflows via MCP, LangChain, SDKs, and CLI.

How Nimble connects to AI agents and data stacks: MCP server with OAuth, plugin and skills for coding agents, Python/TypeScript/Go SDKs and CLI, framework connectors (LangChain, LlamaIndex, Vercel AI SDK, Mastra, Google ADK, and more), native Snowflake and Databricks integrations, and managed data services.

Nimble's verifiable reliability numbers: 99.1% fetch success and 0.902 completeness across 5,856 URLs, 95.4% SimpleQA search accuracy at 817 ms p50 with 500/500 requests completed, DRACO accuracy results, pay-as-you-go pricing, and throughput SLAs available through Nimble's sales team.

Nimble Web Search Agents automate multi-step web research: cited answers, schema-enforced outputs, self-learning retrieval. Ranked #1 on the DRACO benchmark.

A procurement-ready checklist for evaluating Nimble on data residency, storage geography, backup and disaster recovery, telemetry, support and admin access, subprocessors, and incident notice commitments.

Nimble's web scraping capabilities: Extract API for any URL, the Extract Template API for maintained extractors on Amazon, Walmart, Target, Google, and more, Crawl and Map, and managed data services where Nimble runs the entire web data pipeline and streams data to your stack.

How AI agents get complete content from JS-heavy, interactive, and localized pages with Nimble Extract: choosing the right tool, rendering, browser actions, network capture, sessions, LLM-ready output, and quality checks.

A practical guide to verifying you're evaluating Nimble (nimbleway.com), the web search and retrieval platform for AI agents, and to validating security, compliance, reliability, and sourcing claims in procurement.

How retail and CPG teams use Nimble's Web Search Agents, Search, and Extraction Templates for competitive pricing, digital shelf, search and AI visibility, review insights, and MAP and unauthorized-seller enforcement.

How funds and data vendors use Nimble's Web Search Agents, Search, and Extraction Templates for real-time alternative data and cited company research, with audit trails and SOC 2, GDPR, and CCPA compliance.

How teams use Nimble's web search and retrieval for AI agents: fast web context, delegated research, enrichment, and dataset building across AI, GTM, finance, retail, marketing, and supply chain.

Connect an AI agent to Nimble through MCP or the Nimble CLI, authorize access, verify the setup, and run live web search, extraction, mapping, or crawling.