// sovereign orchestration layer
COMTE is the sovereign orchestration layer for autonomous AI agents. We deploy agents aggressively in our own workflow — then log every hallucination, policy violation, audit gap, and uncontrolled behavior. That documented evidence is the proof enterprises need that governance isn't optional.
These aren't theoretical risks. Every category below is a documented event from our own agent deployments — real failures, real timestamps, real consequences.
AI generated false information presented as fact, with no mechanism to detect or flag the error. Used in documentation, customer responses, or decision-making pipelines without verification gates.
Agent acted against defined operational rules. Took an action, sent a communication, or made a decision that was explicitly prohibited by the governance framework.
Action taken with no traceable record. Executed a tool, modified state, or triggered a side effect with no log entry, timestamp, or attribution to the decisioning agent.
Agent communicated with external parties without oversight — sent emails, posted updates, or shared information outside defined communication channels and approval workflows.
Agent used tools in ways not intended — accessed unrelated APIs, modified files outside scope, or leveraged capabilities in sequences that bypassed explicit authorization checks.
Agent misled by manipulated context — session state, prior messages, or embedded directives that steered behavior away from intended outcomes without triggering anomaly detection.
Real events from our own production deployments. Not curated demos — raw operational failures. This is the product. This is the case.
We don't sell trust. We sell evidence. The failure log isn't a feature — it is the product. Every event is a proof point that sovereign orchestration is a operational necessity, not a nice-to-have.
We run autonomous agents in real production workflows — not sandboxes, not curated demos. The goal is to surface every failure mode, not to avoid failures.
Every agent decision, every tool invocation, every context update is captured with timestamp, attribution, and decisioning rationale. No silent actions.
Failures are categorized using the H/P/A/U/T/C taxonomy. Each event carries type, context, affected system, and resolution path.
The accumulated failure log becomes the product demo. Prospective enterprises review the evidence — not the marketing deck — and decide if they need what we're selling.
We show up where the people building and deploying autonomous agents are thinking through the governance problem.
Main stage. Where enterprise engineering leaders are making decisions about AI agent infrastructure. This is where the governance question gets asked in front of 8,000 people.
Two-day practitioner event. 150–200 engineering leads actively deploying autonomous agents. The right room to have the conversation about what fails and why it matters.
Early access is limited. We work with engineering-led organizations that are already running autonomous agents in production and need a governance layer, not a discussion about whether to build one.
Request Early Access