The concepts
the platform runs on.
Fundamentals and architectural principles of the platform.
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Capability-Control Gap
The widening distance between what AI can do and what AI deployments can safely promise.
AI as Infrastructure
The thesis that AI in regulated enterprise is operating infrastructure, not a managed service.
Four Illusions
The four comfortable assumptions about regulated AI that fail under scrutiny.
Four Attributes
The four properties an AI deployment needs to be defensible under regulation: auditable, sovereign, accountable, replayable.
Signal
A single observable event in a business process: a prompt, a tool call, a policy decision, an identity claim.
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Three Primitives
Correlate · Contain · Attest — the core contract every AIOP deployment honours.
Evidence Pack
A cryptographically signed bundle of audit-grade evidence produced as the system runs.
Audit Stream
The append-only, cryptographically signed record of every signal the platform produced.
Determinism & Replay
AI agents follow consistent business processes — every historical decision can be re-executed and verified.
Human in the Loop
Not 'the AI did it' - a named role signs each consequential step, switching from executor to approver.
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8-Layer Architecture
The reference architecture AIOP is built on — identity at the perimeter, evidence at the audit boundary.
Agent Space
The sandboxed execution environment where AIOP-managed agents run.
Open Orchestrator
The model-agnostic router at the heart of AIOP — bring your own models.
Row-Level Compliance
Compliance enforced at the record level, not the application level.