Fiddler AI

AI Observability & Monitoring 📍 Palo Alto, CA Est. 2018

Enterprise AI observability and security platform providing monitoring, guardrails, and control plane for AI agents.

Based in Silicon Valley (Palo Alto, CA), Fiddler AI offers its Fiddler AI Platform as a solution for organizations navigating the complexities of AI agent observability with session replay, debugging, and behavioral tracking. The platform is positioned within the broader AI Observability & Monitoring category, where AI Security Intelligence tracks 32 companies building specialized capabilities.

Founded in 2018, Fiddler AI brings several years of market experience to its current AI security positioning, having evolved its platform through multiple technology cycles.

Why Watch This Company

In the AI observability space, the gap between 'deployed' and 'understood' remains the biggest operational risk for enterprise AI. Fiddler AI addresses this gap through AI agent observability with session replay, debugging, and behavioral tracking — a capability that becomes increasingly critical as AI systems move from experimental deployments to mission-critical production workloads.

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Founded
2018
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Headquarters
Palo Alto, CA
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Category
AI Observability & Monitoring
Key Product
Fiddler AI Platform
Fiddler AI Platform
Enterprise AI observability and security platform providing monitoring, guardrails, and control plane for AI agents.
AI Observability & Monitoring Landscape
AI Observability & Monitoring →
AI Observability & Monitoring provides the instrumentation layer that lets organizations understand what their AI systems are actually doing in production. Unlike traditional application monitoring, AI observability must track model performance, data drift, hallucination rates, latency, cost, prompt-response quality, and behavioral anomalies — metrics that don't exist in conventional observability stacks.
32 companies tracked in this category

Key questions to evaluate any AI Observability & Monitoring vendor — including Fiddler AI:

Does the platform provide real-time monitoring of model performance, including hallucination detection, drift measurement, and response quality scoring?
Can the solution trace full request lifecycles across complex AI chains (RAG pipelines, multi-agent workflows, tool-calling sequences)?
How does the vendor handle cost optimization — can it track and attribute token usage, compute costs, and model efficiency?
Does the platform integrate with your existing observability stack and support OpenTelemetry standards?

Deep-dive intelligence profiles with full market analysis, development timelines, and product breakdowns.

📊 Funding History & Investment Rounds
👤 Executive Team & Key Hires
🎯 Competitive Positioning Matrix
📡 Signal Tracking — M&A, Product, Partnerships
📈 Quarterly Revenue & Growth Metrics
🔗 Supply Chain & Integration Mapping

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Category Peers — AI Observability & Monitoring

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