The Governance Layer for Autonomous Operations.

The control plane for the physical world. Deterministic governance, above every system you already run.

Circular Ontology is the deterministic control plane above operational technology — from factory floors and building automation to controlled-environment agriculture and waste-to-energy. It governs the systems you already run, so every action stays bounded by safety class and backed by evidence.

A comparison chart explaining why running a 5,000°C plasma torch on probabilities is not feasible. The left side shows probabilistic AI with a cloud of smoke labeled "Probabilistic Incumbents [Agents]," and points about generating outputs from learned distributions, hallucinating, and failures. The right side shows deterministic execution with a diagram of a plasma torch releasing a bright flame, labeled "The Deterministic Boundary [Wave 4]," with points about governing decisions with a canonical semantic model and avoiding regulatory violations.

Manifesting The Fourth Wave of AI

Manifesting The Fourth Wave of AI

Mission

To make autonomous operations safe, auditable, and provable — by governing the systems that act on the physical world.

The Thesis — Why Now

A new layer is forming above operational technology(OT)

(OT = Autonomic Industrial Control Systems-Programmable Logic Controllers (AI PLCs)

The Platform

Above your systems, not inside them.

Circular Ontology exists to make autonomous industry governable. We build the deterministic control plane that sits above operational technology, so the systems running factories, buildings, farms, and material-conversion plants can act safely, prove what they did, and remain under human authority as autonomy scales. We do not replace the systems you already run — we make them legible, governable, and defensible.

Each wave of enterprise AI taught software to reason over information. The harder, unsolved problem is reasoning over physical systems — systems that must stay safe, auditable, and deterministic as they act on the world. In high-consequence operations, the cost of a wrong autonomous action is not a poorly worded message; it is a containment failure, an environmental release, or an injury. Probabilistic AI is a poor fit there. The layer that governs matter — deterministically, with machine-enforceable authority and tamper-evident evidence — is still open. Circular Ontology was built to occupy it.

Circular Ontology does not replace your controllers, your building systems, your reactors, or your vendors. It uses deterministic artificial intelligence to govern them — orchestrating heterogeneous operational technology under one deterministic, auditable control plane. It runs on the systems you already operate, alongside hardware from vendors such as Siemens, Allen-Bradley, Tridium, Johnson Controls, Hoogendorn, and Argus Controls Systems so there is nothing to rip out and replace. Every governed action is bounded by safety class. Every decision leaves an evidence trail.

A digital infographic illustrating the need for a semantic control plane to manage AI outputs and prevent cyber-physical risks, featuring flowcharts, icons, and data highlights.

The Four Waves

Diagram illustrating the four waves of enterprise AI migration: foundation builders, agentic platforms, embodied actuation, and ontologies & cyber-physical autonomy, with each wave including descriptions of key features and technological advancements.

•     Wave 1 · Foundation: Analytics — reporting on what happened.

•     Wave 2 · Agentic: Prediction — modeling what comes next.

•     Wave 3 · Actuation: Generation — reasoning over knowledge.

•     Wave 4 · Ontologies: Cyber-Physical Autonomy — governing matter, deterministically. (This is our space.)

Insights — thought leadership by domain

Insights from Circular Ontology on governing autonomy across the systems that run the physical world.

Industrial OT

• Why operational technology needs a governance layer, not another dashboard — the gap every vendor leaves above the controller, and what fills it.

• Deterministic vs. probabilistic: why high-consequence operations can't run on guesswork.

• Governing heterogeneous controllers without ripping and replacing — adding authority and evidence on top of the systems you already run.

Building Automation Systems

• From building data to building truth: auditable control across disparate systems.

• Your platform migration is an opportunity to add governance, not just swap protocols.

•  A common semantic model for buildings: why standards like Brick and ASHRAE 223P matter for governable autonomy.

Controlled Environment Agriculture

• Crop recipes as governed objects: provable compliance for food safety.

• Deterministic governance for living systems — audit-grade control where conditions never stop changing.

• Why CEA is a governance problem as much as a climate problem.

Waste to Energy

•     One governance substrate for every conversion pathway.

•     Reactions at thousands of degrees: why material conversion demands provable autonomy.

•     Turning waste operations into audit-ready, evidence-bearing assets.

Our Team

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Founder CEO: Tim (Tim O) O’Neil

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CITO: Chris Dunn

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CoS: Tim Patterson

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COO: Mark Ludley

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Co-Founder/VP Dina O’Neil

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CAO/GC: Nate Harding

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