An AI that monitors your AI. Continuous behavioral scoring of every agent action — with automatic isolation when something goes wrong.
Overseer AI learns what normal looks like for each agent — then catches everything that isn't
Over 7 days, Overseer AI establishes a behavioral baseline for each agent type — what tools it calls, how often, in what sequence, and at what volume.
Every tool call is scored in real time against the baseline. Anomaly scores factor in tool type, parameter values, call frequency, time of day, and session context.
When an agent deviates beyond its threshold — scope escalation, unusual external calls, out-of-pattern payment requests — Overseer flags it immediately.
The agent is automatically isolated. No further tool calls permitted. SOC receives a full alert with session context, agent ID, prompt chain, and anomaly scores.
Behavioral intelligence that no rule-based system can match
Each agent type gets its own behavioral profile. A payment agent and a customer service agent have different normal — Overseer knows the difference.
Every tool call scored against baseline in under 5ms. Anomaly scores compound across a session — a single unusual call is noted, a pattern of them triggers containment.
When anomaly score exceeds threshold, the agent is isolated in milliseconds — no SOC analyst required. No human button-push. The Kill Switch fires autonomously.
Detects when an agent attempts to access tools, data, or permissions it was never authorized to use — the hallmark of a compromised or manipulated agent.
When an orchestrator spawns child agents, Overseer tracks the full chain — inherited permissions, tool calls, and behavioral deviation across the entire agent tree.
Surfaces model drift and adversarial inputs automatically. Every model input and output is captured for ongoing validation — satisfying OCC SR 11-7 requirements.
Behavioral anomalies that rule-based systems miss entirely
Agent attempts to call tools or access data beyond its authorized scope after receiving a manipulated prompt
Payment agent deviates from baseline — unusual amounts, frequencies, destinations, or time-of-day patterns
Agent references external domains or attempts HTTP calls it has never made before — a zero-baseline deviation
Unauthorized agents operating outside governance frameworks, detected via behavioral fingerprinting against known agent profiles
Automated non-human sessions with credential-seeking prompts — the signature of hijacked CLI tools and supply chain attacks
Continuous monitoring for inputs designed to shift model behavior over time — slow-burn attacks invisible to point-in-time checks
From prompt injection to containment in 13 seconds
Schedule a technical session to see behavioral security against your actual AI agent infrastructure