Fiddler AI (LLM & Agent Governance)
Overview
Enterprise AI control plane for monitoring, evaluating, enforcing policy, and governing LLM agents and predictive models.
Fiddler AI provides an enterprise AI control plane for agentic and predictive AI systems. It focuses on production visibility, continuous evaluations, agentic observability, policy enforcement, AI governance, ML observability, and cost controls for evaluation and guardrail workflows. The platform is positioned for enterprises that need centralized oversight of agent behavior, model performance, enforcement decisions, sensitive-data handling, and AI governance across regulated or high-stakes deployments.
AI Agent Store research
What the evidence says about Fiddler AI (LLM & Agent Governance)
Fiddler AI is positioned as an enterprise control plane for both agentic AI and predictive AI, combining evaluations, observability, policy enforcement, governance, and cost-efficiency tooling. Its most distinctive fit is for organizations that need centralized operational oversight and auditability across production agents, model behavior, sensitive-data controls, and AI governance processes.
Verified September 1, 2026
Verified capabilities
- Continuous evaluations
Supports in-environment evaluation from testing to production for agentic AI workflows.[1]
- Agentic observability
Provides end-to-end visibility, context, and control for the agentic lifecycle, including a mission-control-style view of agents and visibility into actions, tokens, and cost by user and team.[1]
- Policy enforcement and guardrails
Enforces enterprise AI policies and supports guardrail workflows, including inline handling at request and response paths for coding agents.[1]
- AI governance, risk, and compliance
Provides centralized control and accountability for enterprise AI governance and compliance, with auditable enforcement decisions that record who triggered an event and what happened.[1]
- ML observability for predictive AI
Includes ML observability for operating predictive AI models at scale alongside agentic AI use cases.[1]
- Evaluation cost controls with Fiddler Centor Models
The official page says Fiddler Centor Models power evaluations and real-time policy enforcement in-environment without external LLM API calls, reducing evaluation TCO by up to 98% compared with foundation models.[1]
Where it fits best
- Enterprises running production LLM or agentic systems that need continuous evaluations, agentic observability, policy enforcement, and AI governance in a centralized control plane.[1]
- Organizations in regulated or high-stakes sectors such as government, financial services, healthcare, and insurance, which are explicitly listed as solution areas on the official site.[1]
Buying and deployment notes
The official context references Pricing Plans and Contact Sales, but no public starting price, billing period, or packaged plan details are provided in the supplied source.[1]
Platforms: Enterprise AI control plane, Agentic AI workflows, Predictive AI workflows[1]
Deployment: Commercial product with request-demo and contact-sales access, Gateway-based coding-agent workflow described in the official demo[1]
Important considerations
- The supplied official context points users to pricing plans and Contact Sales / Request demo flows, but it does not provide a public starting price.[1]
- The product is presented as an enterprise AI control plane, so buyers looking for a lightweight self-serve tool should confirm packaging, onboarding, and deployment fit with Fiddler sales.[1]
Sources and research method (1)
We record only claims tied to public sources checked by our team or listing workflow. Counts above are derived directly from this profile, not a subjective rating.
- Fiddler AI: The AI Control Plane for the Enterprise Agent WorkforceOfficial site · checked 2026-09-01
Autonomy level
48%
Comparisons
Custom Comparisons
Some of the use cases of Fiddler AI (LLM & Agent Governance):
- Monitoring production LLM and agentic applications
- Evaluating agents from testing through production
- Enforcing AI policies and guardrails
- Tracking token usage, actions, and AI spend across teams
- Managing AI governance, risk, and compliance workflows
- Observing predictive ML models in production
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Popularity level: 59%
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