Autonomous systems need a control plane.

As AI moved from assistants into autonomous actors — taking actions, calling tools, chaining decisions across enterprise systems, edge devices, and clinical infrastructure — the gap between "what we intended" and "what actually ran" became a serious liability. Chronicle exists to close that gap.

The problem

Enterprises are shipping AI products quickly — but when something goes wrong, they have no way to answer basic questions: Why did the model say that? Which policy applied? What chain of events led here? Can we prove the decision was made correctly?

The same is true in healthcare, manufacturing, energy, and anywhere autonomous systems make consequential decisions. The decision moment is unmonitored. Evidence disappears. Causality is reconstructed after the fact, if at all.

Traditional observability tools were built for deterministic software. Autonomous systems aren't deterministic. They make decisions — and those decisions carry risk, intent, and causality that logs can't capture.

What we built

Chronicle is a decision control plane — not a logging tool, not a monitoring dashboard. It sits in-line with your AI systems, enforcing policies before decisions are finalized, recording tamper-evident evidence of every call, and surfacing intelligence that compounds over time.

The architecture is split deliberately: a lightweight Rust runtime on your infrastructure handles enforcement and evidence capture at sub-millisecond latency, while our cloud platform handles intelligence aggregation and query at scale.

Your evidence never leaves your environment in plaintext. We designed it this way from day one — not as a feature, but as an architectural constraint.

How we think about the problem

Control at the source

Enforcement happens at the decision boundary — not in the postmortem. Chronicle intercepts every decision before it executes, applying your policies in real time.

Evidence that holds up

Tamper-evident records built for compliance, audits, and governance. Every decision is attributable, timestamped, and cryptographically sealed.

Any system, any scale

From LLM orchestrators to edge inference, clinical AI to IoT controllers — Chronicle is designed for the breadth of autonomous systems, not just enterprise chatbots.

Intelligence compounds

Behavioral baselines, drift detection, and shadow AI visibility emerge from the data you're already collecting. Every day Chronicle runs, it understands your systems better.

STOE

STOE is an enterprise AI infrastructure company. Chronicle is our flagship product. We're focused on the operational layer that makes autonomous AI systems safe to deploy at scale — the layer most enterprises are building themselves, badly, one incident at a time.

We believe the market for autonomous system governance is much larger than the "enterprise AI" framing suggests. Every domain that uses AI to make decisions — healthcare, manufacturing, infrastructure, logistics, legal — eventually needs what Chronicle provides.

We're building the control plane that every autonomous system will eventually require.

At a glance

ProductChronicle v2
FocusAutonomous systems
RuntimeRust (client) + Python (cloud)
DeploymentOn-prem + cloud
EvidenceClient-side encrypted
StageEarly access

Want to talk to the team?

Chronicle is available for enterprise teams. We'd like to understand your use case first.

Get in touch