Fiddler AI

Fiddler AI is an enterprise AI observability and security platform, positioning itself as a neutral control plane for compound AI systems as organizations move autonomous agents into business critical workflows. Founded in 2018 in Palo Alto, the company built early expertise in model explainability and root cause analysis, and in January 2026 raised a thirty million dollar Series C led by RPS Ventures, bringing total funding above sixty million dollars. Fortune 500 organizations including Nielsen use Fiddler to establish trust, safety, and security across agentic, large language model, and traditional machine learning deployments.

The platform unifies evaluation, monitoring, and governance across the full lifecycle. For agents it provides hierarchical visibility from application to session to agent to trace to span, and for predictive machine learning it surfaces inputs, predictions, and explanations. Teams select from more than a hundred out of the box and custom metrics, including hallucination, toxicity, PII and PHI detection, drift, performance, and industry specific business measures, with deep diagnostics that reveal the root causes of agent failures and model degradation.

Security is a first class concern. The Fiddler Trust Service provides quality and moderation controls powered by task specific Fiddler developed Trust Models, which the company positions as the fastest guardrails in the industry, applying real time protection against harmful exposure. The platform supports fairness and bias detection, audit trails for regulated industries, and governance suited to GDPR and HIPAA obligations. Deployment options include cloud and VPC, so sensitive data can stay within a controlled environment.

Fiddler is an enterprise product with pricing available through sales, offered in Lite, Business, and Premium tiers and billed on consumption such as data ingested, number of models, and metrics rather than per host. There is no public free tier, which makes it a fit for regulated enterprises rather than individual developers or small budget constrained teams.