AI agents are writing production code today. ASE is the self-hosted operational control plane that defines their boundaries, supervises their execution in real time, and produces an immutable evidence trail to prove compliance.
Built for engineering leaders, security teams, and compliance officers responsible for the code AI ships into production.
See ASE running against a real repo. No deck.
ASE brings to agentic delivery what regulated workflow automation brought to business operations: identity boundaries, versioned definitions, approvals, immutable audit, evidence reporting, and recovery paths — in one product surface your engineering and compliance teams can both stand behind.
Copilot, Cursor, Claude Code, and custom agent scripts are writing and refactoring code in your codebase right now. None of that activity is captured in your existing change-control database.
Prompts are ad-hoc. Reviews are manual and best-effort. Event logs are scattered across vendors. There is no single, chain-hashed record of what the agents decided, which models were invoked, and who approved the changes.
ASE establishes the central control plane for multi-agent execution. It captures work definitions, approval gates, runtime leases, and tamper-evident audit trails that map directly to your existing IT controls and regulatory requirements.
ASE is not a prompt-chain runner. It sits above your code-intelligence providers, your live coordination service, your graph evidence store, and your model-specific coding agents — and gives the engineering lead one product surface for the full lifecycle of an agent constellation working on a real codebase.
Each authority boundary is a contract, not a black box — you can swap providers without rewriting your control plane.
The first useful ASE slice lets an operator stand up a small agent constellation against a single repository — with the controls and evidence you'd expect for production work.
Your source code, your compliance posture, your identity authority. ASE deploys inside your network alongside the rest of your engineering stack — no agentic activity, evidence, or definitions leave your perimeter unless you choose to export them.
For regulated workloads, this is not a nice-to-have. Auditors need to see who approved what, what evidence was captured, and what the agent constellation actually did — with the same trust model you already apply to humans on the same codebase.
ASE is in active development at Beyond Ordinary. If you’re trying to operationalize coding agents against a real, regulated codebase, the 30-minute walkthrough is the fastest way to see whether ASE fits your stack.