Fiddler AI is an AI Control Plane offering real-time guardrails, observability, evaluation, and governance for enterprise AI agents and models.
Category
AI Infrastructure & MLOps
Pricing
Free plan with basic real-time guardrails; Developer plan priced at $0.002 per trace with unified observability, custom evaluators, and SSO; and a custom-priced Enterprise plan with flexible SaaS/VPC/on-premise deployment and dedicated support (fiddler.ai/pricing)., from $30
Verified
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Last updated
August 6, 2026
SaaSEnterpriseAPIAI
Fiddler AI provides an AI Control Plane built to help large organizations monitor, evaluate, secure, and govern AI agents and machine learning models from development through production. The platform combines unified observability — a single dashboard tracking every deployed agent's performance with per-user and per-team analytics — with inline policy enforcement that detects and blocks PII, PHI, secrets, prompt injection, and jailbreak attempts in under 80 milliseconds. Fiddler's proprietary Centor Models run evaluations in-environment rather than routing every check through an external foundation model, which the company says cuts evaluation costs by up to 98%. Fiddler is used by Fortune 100 organizations in regulated, high-stakes industries — including financial services, healthcare, insurance, and government — where teams need auditable evidence of how AI systems make decisions. It integrates with major ML and LLM infrastructure such as Amazon SageMaker AI, Google Cloud Vertex AI, Azure OpenAI, Amazon Bedrock, Databricks, Datadog, NVIDIA NIM/NeMo Guardrails, and LangGraph, and can be deployed as SaaS, in a customer's VPC, or on-premise.
Key Features
Unified AI observability dashboard — A single dashboard tracking every deployed AI agent's performance, with per-user and per-team analytics.
Real-time guardrails — Inline policy enforcement in under 80ms that detects and blocks PII, PHI, secrets, prompt injection, and jailbreak attempts before they reach production.
Fiddler Centor Models — Proprietary, in-environment evaluation models that Fiddler says reduce evaluation costs by up to 98% compared to routing every check through an external foundation model.
Compliance audit trail — Records all enforcement decisions to provide auditable evidence for regulatory compliance and risk management.
Flexible deployment — Deploy as SaaS, in a customer's VPC, or fully on-premise for enterprises with strict data residency requirements.
Broad AI infrastructure integrations — Connects with Amazon SageMaker AI, Google Cloud Vertex AI, Azure OpenAI, Amazon Bedrock, Databricks, Datadog, NVIDIA NIM/NeMo Guardrails, and LangGraph.
Pros & Cons
Pros
Real-time guardrails operate in under 80ms, enabling inline blocking of harmful outputs rather than after-the-fact detection
Proprietary Centor Models reduce evaluation costs versus routing every check through a third-party foundation model
Unified dashboard covers both agentic and predictive AI systems across the full development-to-production lifecycle
Flexible deployment (SaaS, VPC, or on-premise) suits enterprises with strict data residency or compliance requirements
Free tier lets teams try core guardrails before committing to a paid plan
Cons
Detailed, transparent pricing is limited to a single per-trace rate for the Developer plan; Enterprise pricing requires contacting sales
Enterprise-grade features like SSO, dedicated support, and on-prem deployment are gated behind higher tiers, which may be costly for smaller teams
Primarily built for large, regulated organizations, so the depth of tooling may exceed what smaller teams or individual developers need