Fiddler AI, a Palo Alto, California-based provider of an enterprise AI observability and security platform, has raised $30 milliuon in Series C funding led by RPS Ventures.
The round also saw participation from existing investors Lightspeed Venture Partners, Lux Capital, Insight Partners, Capgemini Ventures, Dallas VC, Dentsu Ventures, and Mozilla Ventures, as well as new investors LG Technology Ventures, Benhamou Global Ventures, and LDV Partners.
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The company, which has raised $100 million to date, plans to use the funds to expand operations and scale its platform across regulated industries, including healthcare, financial services, and insurance.
The funding accelerates Fiddler’s vision to become the neutral control plane for compound AI systems as enterprises increasingly incorporate autonomous agents into business-critical workflows. The Fiddler Control Plane will deliver standardized telemetry, reliable evaluation, continuous monitoring, enforceable policy and auditable governance across the AI lifecycle.
“The explosion of AI tools has created a major gap in enterprise governance,” said Timothy Murphy, Partner at RPS Ventures. Companies are deploying agents that interact with customers and make critical decisions yet monitoring relies on fragmented solutions designed for simpler deterministic tasks. A single agentic workflow can involve dozens of handoffs between models, tools, and APIs each a potential point of failure. Fiddler is the first company to offer an actual control plane, providing complete visibility into agent actions, contextual intelligence into why they behave the way they do, and real-time controls to enforce policy and prevent failures. That category-defining position is why we led this round.”
Unlike point solutions that focus only on developer-level debugging, fail to provide a holistic view of AI systems, or rely on external models for evaluation and custom metrics, Fiddler is a fully “batteries included” platform. Its proprietary trust models deliver accuracy, safety and compliance out of the box, enabling enterprises to deploy agentic and predictive AI at scale.
“Fiddler provides unified observability, protection and governance across agents and predictive models, making it central to our AI strategy,” said Karthik Rao, CEO of Nielsen. “We are especially excited for the upcoming rollout of the control plane and the intelligent orchestration it will bring as our AI footprint expands.”
“Building trust into AI has been our mission from day one—ensuring systems perform as expected, risks are managed proactively, and AI investments deliver measurable returns,” continued Gade. “We’re grateful to RPS Ventures and our investors for supporting that mission as agents become central to enterprise operations. The control plane for compound AI systems is how we provide trust at scale.”
The governance gap has serious consequences, as agent failures can lead to regulatory fines, legal risks and brand damage. These high stakes are driving rapid enterprise adoption of Fiddler especially in regulated industries where AI oversight is critical. The company has grown revenue more than fourfold in the past 18 months and recently achieved AWS Pattern Partners status. Fiddler was also named the #1 company in AI Agent Security & Risk Management by CB Insights.
About Fiddler AI
Founded in 2018 by Krishna Gade, Fiddler is an all-in-one AI observability and security platform for responsible AI. The platform provides evaluation, monitoring, and analytics to give teams visibility, , and control across development and production, helping them build reliable AI agents, GenAI, and ML applications. The Fiddler Trust Service, a core part of the platform, delivers quality and moderation controls using scalable, task-specific Trust Models, providing some of the fastest AI guardrails in the industry. Fiddler also offers flexible, secure deployment options via cloud and VPC environments.
Fortune 500 companies use Fiddler to scale AI agents, GenAI, and ML deployments, ensuring high performance, reducing AI risks, and maximizing ROI.
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