AI observability / monitoring
Fiddler, Arthur
Telemetry and alerts on models in production.
Stops the decision (not just watches it); lending-specific; examiner evidence.
Observe vs. enforce.
Most AI-governance tools watch. Sentinel stops.
Observability tells you a bad decision happened. A registry documents that a model exists. Sentinel is a decision gate in the path of execution — it returns APPROVE, BLOCK, FLAG, or ESCALATE before the agent acts, so every lending decision is examiner-defensible.
Not observability. Not a registry. Enforcement — before execution.
Category
Examples
What they do
What Sentinel does that they don’t
AI governance registry / GRC
Credo AI, Holistic AI, OneTrust, IBM
Model inventory, policy, risk reports, lifecycle.
Enforces at runtime (not just documents); built for the lending exam.
Stop a bad path in minutes?
Most tools: escalate a ticket
Alerts and dashboards after the fact; rarely a named runtime kill switch.
Accountable kill switch — global, agent type, or agent id — checked first in the path.
Gate releases on held-out evals?
Most tools: optional CI checks
Model cards and offline tests; production policy change often uncoupled.
Release-gated eval sets with pass-rate / latency / critical-regression thresholds before ship.
Sentinel
—
Inline decision gate: APPROVE / BLOCK / FLAG / ESCALATE before execution.
Enforcement + kill switch + eval gates + QA disagreement + hash-chained evidence.
Observability and registries are real and useful — but they sit beside the decision, not in front of it. Sentinel is the only layer that blocks the wrong AI lending decision before it executes, can stop a governed path in minutes, gates releases on held-out evals, and hands an examiner a tamper-evident evidence trail that proves it.
Get Started
Put a control plane in front of your AI agents.
Start with a governed demo, or see the full 11-stage decision pipeline on the home page.