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AI's New Frontier: Nimble Powers Web Data for Machines
25 Feb
Summary
- Nimble's platform transforms the web into trusted data for AI.
- Company secured $47 million in Series B funding.
- The technology uses a multi-agent architecture for data validation.
Nimble has introduced its Agentic Search Platform, a system engineered to transform the public web into decision-grade data for AI applications and business processes. The company announced this launch alongside securing $47 million in Series B funding, bringing its total raised to $75 million. This platform addresses a critical bottleneck in AI development: the unreliability of external data often used by large language models.
The core of Nimble's solution is a proprietary distributed architecture featuring specialized agents. These agents navigate, parse, process, and validate live internet data in real time. Unlike traditional search engines, this multi-agent system leverages advanced reasoning capabilities from frontier models to control browsers, cross-check results, and produce auditable data outputs with over 99% accuracy.
Nimble's platform offers a different approach compared to consumer search engines like Google. While general search tools are optimized for speed and broad answers, Nimble focuses on delivering high-scale, high-accuracy, granular data essential for enterprises making significant decisions. The platform is model-agnostic, integrating seamlessly with AI models from OpenAI, Anthropic, and Google's Gemini, and is designed for enterprise scalability with robust governance and compliance certifications including SOC2 Type II, GDPR, CCPA, and HIPAA.
