Pre-deployment evals and static guardrails are necessary, but they aren’t enough for autonomous systems. ChatSee provides Runtime Behavioral Assurance—the continuous observation and governance required to scale AI agents safely in production.
The New Layer of Enterprise Oversight
Autonomous agents are no longer experimental; they are embedded in your core workflows. But as autonomy expands, control gaps widen. ChatSee provides Runtime Behavioral Assurance—the missing layer between your agentic runtimes and enterprise oversight.
Ingest runtime events through a flexible, multi-path architecture including direct SDK instrumentation, gateway proxies, and MCP endpoint integration.
ChatSee enhances telemetry with a detailed failure taxonomy, classifying specific anomalies like tool misuse and policy deviations for clear risk.
ChatSee improves agent performance by transforming past errors into persistent remediation rules that prevent hallucinations and recurring failures.
Foundation Models
Agent Frameworks
Observability & SIEM
Cloud Platforms
Stop wasting engineering cycles building custom monitoring tools. ChatSee is a plug-and-play watchtower that allows developers and leaders to monitor, remediate, and enhance agents in real-time, drastically accelerating your production timeline.
Stop manual log-diving by automating failure investigation and root-cause analysis for autonomous agent systems.
Protect brand equity and revenue by detecting behavioral anomalies before they scale into production failures.
Accelerate your AI roadmap by replacing fear-based manual oversight with scalable, policy-gated runtime assurance.
Convert transient production errors into structured Failure Memory to optimize prompt tuning and retraining loops.
Minimize audit overhead with automated behavioral history and real-time verification of your active guardrail protocols.
Stop managing "unknown unknowns" and start scaling with absolute oversight. Move your agents from experimental pilots to governed enterprise infrastructure by closing the runtime control gap today.
