Foil – AI agent monitoring with behavioral context

Summary: Foil is an AI-powered observability tool that monitors other AI agents by learning their behavior and responsibilities through evolving agent profiles. It detects issues like hallucinations, behavioral drift, and grounding failures with contextual insights rather than simple logs, enabling targeted health checks and real-time problem detection.

What it does

Foil automatically creates dynamic profiles for each AI agent, tracking tool usage, error rates, and traffic patterns to establish baselines. It generates health checks called anchors, performs natural language queries across agents and traces, and detects anomalies such as loops, prompt injection, and PII leakage in real time.

Who it's for

Foil is designed for developers and teams managing multiple AI agents who need automated, contextual monitoring to reduce manual trace analysis and improve agent reliability.

Why it matters

It addresses the challenge of manually interpreting large volumes of logs and traces by providing automated, context-aware detection and diagnostics tailored to each agent’s unique behavior.