<340 ns Per decision
<600 ps Logical op
2.9M/sec Throughput
On-premise native No cloud runtime

Architecture Principles

The foundational principles that govern the structural design of the decision infrastructure.

Deterministic Resolution Model

The resolution model produces identical outcomes given identical inputs, policy version, and evidence set. There is no stochastic component, no weighted scoring, and no contextual reinterpretation of inputs. The evaluation function is a pure mapping from structured inputs to structured outputs. This determinism is a compile-time guarantee, not a runtime aspiration. Any given evaluation can be independently reproduced by any party with access to the same inputs and policy definition.

Evidence Accumulation

Evidence is submitted, timestamped, and sealed before it participates in any evaluation. Each piece of evidence is an immutable record. Evidence accumulates over the lifecycle of a decision — it is never replaced, overwritten, or retroactively modified. The evidence set at the time of resolution constitutes the complete and verifiable basis for the outcome. No external data source, implicit assumption, or unregistered input influences the evaluation.

Governance Thresholds

Resolution outcomes are determined by governance thresholds defined in the policy layer. Thresholds are explicit, auditable, and versioned. They define the conditions under which evidence is sufficient to produce a definitive resolution versus an indeterminate outcome. Threshold modification follows a controlled governance process with full version history. No threshold change takes effect retroactively — all prior resolutions remain bound to the threshold configuration active at the time of evaluation.

Human Oversight

The infrastructure produces structured evaluation outputs that inform human operators. It does not autonomously execute consequences, trigger external actions, or enforce outcomes without explicit human authorization. Indeterminate results — where evidence is insufficient for definitive resolution — are surfaced as a first-class outcome type, specifically designed to require human review. The system is an instrument of human decision-making, not a substitute for it.

Audit Trace Integrity

Every evaluation, every piece of submitted evidence, and every policy version change is recorded in an append-only audit trace. Runtime services can only insert records — they cannot update or delete existing entries. Revocations are represented as new records, not as deletions. The audit trace provides a complete, chronologically ordered, and tamper-evident history of all system activity. This integrity is enforced at the database level through role-based access controls and schema constraints, independent of application logic.

No Probabilistic Inference Without Threshold

The infrastructure does not employ probabilistic inference, statistical modeling, or machine learning to determine evaluation outcomes. Where probability or confidence measures are associated with evidence, they are treated as structured input data — not as decision-making mechanisms. The resolution function applies deterministic logic against governance thresholds. There is no implicit weighting, no Bayesian updating, and no gradient-based optimization in the evaluation path. Every outcome is the direct consequence of policy rules applied to evidence, with no intermediate probabilistic layer.

Review the security architecture

The architectural principles are reinforced by structural security controls at every layer of the infrastructure.

Security Architecture

Three-Layer Architecture

OmegaOS is structured as three distinct, composable layers. Each layer has a defined scope, clear boundaries, and explicit interfaces.

Layer 1 — Execution Governance Layer

The deterministic evaluation engine. Receives authorization requests, evaluates them against registered evidence and policy, and produces three-state outcomes (Allow / Deny / Indeterminate). All outcomes are recorded in the append-only ledger. This layer does not execute consequences — it produces structured decisions.

Layer 2 — Evidence & Compliance Layer

The audit and attestation layer. Manages evidence submission, proof chain assembly, and Evidence Pack export. Produces JSONL artifacts with SHA-256 integrity hashes and optional Ed25519 attestation. Evidence Packs are self-contained and verifiable offline — no system access required by the auditor.

Layer 3 — Policy Enforcement & Human Oversight Layer

The governance and oversight interface. Surfaces Indeterminate outcomes for human review. Manages policy versioning, governance thresholds, and mode transitions (Observe → Shadow → Enforce). Human operators retain full authority over enforcement decisions. The system is an instrument of human decision-making, not a substitute for it.