AgentOps

AI Observability & Monitoring 📍 San Francisco, CA Est. 2024

Developer platform for monitoring, testing, and debugging AI agents with session replays and cost tracking.

Based in Silicon Valley (San Francisco, CA), AgentOps offers its AgentOps 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 2024, AgentOps is among the newest entrants in the AI Observability & Monitoring space, building its approach from the ground up to address the current generation of AI security challenges.

Why Watch This Company

In the AI observability space, the gap between 'deployed' and 'understood' remains the biggest operational risk for enterprise AI. AgentOps 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
2024
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Headquarters
San Francisco, CA
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Category
AI Observability & Monitoring
Key Product
AgentOps Platform
AgentOps Platform
Developer platform for monitoring, testing, and debugging AI agents with session replays and cost tracking.
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 AgentOps:

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

31 other companies in this category

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