Kernel is the runtime behavior control layer for AI agents performing consequential financial actions.
Financial decisions are increasingly automated. Existing controls validate individual actions, but they do not detect gradual behavioral change across many decisions.
Companies are adopting agents because labor is expensive, reviews don't scale, approvals create bottlenecks, and AI is becoming cheaper every quarter. Autonomous workflows will increase regardless of whether they're perfect.
Kernel watches every agent action over time. When behavior changes, Kernel decides before money moves:ALLOW,REVIEW, orBLOCK. Operators inspect flagged actions, and every outcome is recorded.
Kernel sits between the agent and the business system, so every consequential action can be checked before it becomes irreversible.
Kernel shows its work through live traces, benchmark data, and recorded evaluation history. The evidence is attached to the product, not separated from it.
In the latest benchmark aggregate, models under financial pressure still drifted in 85.2% of trajectories, typically within 3–5 sessions. The chart below shows per-model drift rates across all four scenarios, which is more useful than a single scenario slice because it highlights both reliable failure and partial resistance.
Policy engines validate individual requests against static rules. Fraud detection scores transactions. Observability shows what happened. None of them detect whether an agent's behavior is gradually changing over time.
Kernel's runtime evaluation, investigation, and history surfaces give every team visibility into agent behavior.
Every claim is backed by benchmark data, product traces, and evaluation history you can inspect directly.
Security, deployment modes, and audit documentation are maintained separately for procurement and engineering review.
Integration guides, API reference, and deployment docs cover every path — from hosted API to self-hosted stack.
Kernel runs alongside existing AI systems. No workflow changes. No model retraining. No agent rewrites. Begin by observing behavior. Enable intervention only when you're ready.
Design partners, contact, and company context — available when you want them.