About ARX
The operating system for enterprise AI.
ARX is the control plane every AI workload at a regulated enterprise runs on. Credit, fraud, pricing, clinical, and operational models plug into one governed platform that remembers what each model knows, routes work to the right model at the right cost, and proves cognition is preserved when models swap.
Memory, routing, policy, coordination, and verification come as one runtime rather than five vendor stacks. The evidence an auditor needs for EU AI Act Article 9, SR 11-7, FedRAMP, or DoDD 3000.09 is a byproduct of the runtime executing, not a quarterly reconstruction project.
The Thesis
Governance belongs in the substrate, not in a separate workflow.
Providers sell the model. The enterprise owns the regulator, the board, and the incident. Memory, routing, policy, and verification have to sit on a runtime that is neutral across providers and persistent across model swaps.
The moat is mathematics. Cross-model fidelity is verified with machine-checkable certificates, fidelity certificates are cryptographically signed, and an auditor can re-verify the math without re-running the model. The IP is theorems, not trade secrets.
Built, not roadmapped
The runtime is already in production.
Tested under load
The gateway runs against a production-scale test suite that covers every step of the request path, every policy boundary, and every cross-model transfer. The runtime is not a demo.
Mapped to the regulator
The audit chain a federal program needs is the audit chain a regulated bank already requires. Same telemetry, mapped once, reused across EU AI Act, FS AI RMF, SR 11-7, FedRAMP, and CMMC.
Patent pending
Trust Vectorization, the cross-model fidelity layer underneath the gateway, is the subject of an active provisional patent. The IP is theorems, not trade secrets.
How We Build
Research to production in weeks rather than quarters.
Most organizations separate researchers from engineers. Scientists publish, engineers ship, and somewhere in between the insight gets diluted, delayed, or lost. ARX rejects that split.
Scientists and engineers share a codebase and a constraint. Research that cannot survive real workloads, real latency budgets, and real failure modes is research that has not been finished. The specification is the contract, and the runtime is the proof.
Formal proofs become production services, fidelity bounds are tested against adversarial data before they are claimed, and the gap between what is known and what ships is measured in weeks.
Specification
Every capability begins as a formal specification with mathematical bounds, correctness proofs, and defined failure modes. The specification is the contract, and the implementation follows.
Validation
Theoretical guarantees are tested against production-scale data before any claim is made externally. If a fidelity bound is stated, the test suite proves it under adversarial conditions.
Deployment
Production is the only environment that matters. Canary deployments, automated rollbacks, continuous fidelity monitoring. If it works in staging but not in production, it does not work.
Convictions
Four convictions that shape the platform.
The moat is mathematics.
Code gets replicated. Features get cloned. Machine-checkable proofs of cross-provider fidelity do not. The IP is theorems, not trade secrets.
Statefulness is non-negotiable.
Stateless AI is disposable AI. If context does not persist across sessions, cross providers, and stay verifiable at every step, the enterprise owns a demo rather than infrastructure.
If you cannot audit it, you cannot trust it.
Regulated industries do not get to hope the AI is compliant. They have to prove it. Governance belongs in the architecture itself so the evidence falls out of normal operations, not out of a quarterly reconstruction project.
Demonstrate, never announce.
No roadmap decks, no pre-announced capabilities. Every claim on this site can be demonstrated against real data at production scale. If it is not in production, it is not real.
Scientists, engineers, and operators working together under one roof.
Meet the team →One runtime.
Every model. Every audit.
If there is space in your schedule over the coming weeks, we would welcome a conversation with your team.
Connect with the team
The control plane
for enterprise AI.