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Fiddler AI

Fiddler AI is a commercial AI observability and governance platform for agents, LLMs and ML models, with guardrails, evaluations and monitoring; CrowdStrike has announced it will acquire Fiddler.

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Introduction

Fiddler AI positions itself as an AI control plane: a system of trust for the agentic lifecycle. Its site lists understanding every agent decision, enforcing enterprise AI policies with fast guardrails, centralised governance and compliance, and fast, cost-effective models for evaluation.

The platform covers ML model monitoring, explainability, LLM and agent observability, and guardrails. Its homepage announces that CrowdStrike is to acquire Fiddler to deliver agent observability, so product packaging may change.

In the quality loop Fiddler is a production monitoring and governance layer.

Teams evaluating it should confirm how the acquisition affects contracts and roadmaps.

Features

  1. Agent observability: Trace agent decisions.
  2. Guardrails: Policy enforcement.
  3. Evaluations: Purpose-built evaluation models.
  4. ML monitoring: Drift and performance.
  5. Explainability: Model explanations.
  6. Governance: Compliance reporting.

Pros

  1. Enterprise focus: Governance and compliance features.

Cons

  1. Acquisition pending: CrowdStrike deal may change packaging.
  2. Enterprise pricing: Larger plans via sales.
  3. Hosted: Data goes to the platform.
  1. Sign up for the free plan.
  2. Instrument your agent or model with Fiddler’s SDK.
  3. Configure guardrails and monitoring alerts.

Resources:

Pricing

Fiddler’s pricing page lists a Free plan, usage pricing of $0.002 per trace for the next tier, and enterprise plans through sales.

  1. Enterprises needing AI governance and monitoring.

Conclusion

Fiddler offers broad AI observability and governance.

Watch for changes as the CrowdStrike acquisition proceeds.

On CheckOps, Fiddler AI is filed under the Production monitoring & observability stage. Related tools listed here include Langfuse, Laminar, Helicone, OpenLLMetry, AgentOps and Arize Phoenix. A short trial on a real project, with your own code, data and pipeline, is usually the fastest way to choose between them, because fit matters more than feature lists. Facts here come from the official site, documentation and repository, checked on 11 November 2026.

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