Governance Infrastructure Features

Deterministic AI governance enforcement backed by 90 filed U.S. provisional patent applications. Every inference verified, every decision auditable, every veto architecturally enforced.

Three-Layer Trust Infrastructure

EVE AI Core separates governance into three isolated execution planes. Each plane operates independently so that a failure in one cannot compromise the others. This architecture ensures that policy enforcement, runtime execution, and evidence collection are structurally decoupled.

Architectural Separation

Standard AI systems apply safety checks inline with generation. EVE AI Core enforces governance across three physically separated planes, each with its own data path and failure domain.

  • Authority Resolution Layer (Pre-Inference): Policy evaluation, Charter compliance checks, dangerous content detection, and intent classification execute BEFORE any LLM call. Blocked requests never reach the model.
  • Governed Inference Layer (Runtime): Circuit Breaker state management, CRD scoring, Trust Dial gating, and veto engine enforcement operate during inference. Non-compliant outputs are intercepted mid-stream.
  • Cryptographic Authority Chain Layer (Post-Inference): Cryptographic attestation, hash-chain audit trail, Brier score calibration, and compliance reporting execute after every response. Every decision is recorded with full provenance.

Control Plane

Pre-inference policy enforcement. Charter rules, dangerous content patterns, and intent classification block prohibited requests before they reach the LLM.

Execution Plane

Runtime enforcement. Circuit Breaker monitors provider health, CRD scoring evaluates output confidence, and the Veto Engine intercepts non-compliant generation.

Evidence Plane

Post-inference audit. HMAC-SHA256 attestations, SHA-256 hash-chain ledger, and calibration tracking produce tamper-evident compliance records.

TVE Pipeline (Telemetry Verification Engine)

The TVE Pipeline is the core enforcement path. Every request and response passes through 8 sequential verification stages. No stage can be bypassed. Each stage produces a typed verdict that feeds the next.

8-Stage Verification Flow

1. Intent Classification 2. Charter Compliance 3. Circuit Breaker 4. Truth Store 5. CRD Scoring 6. Veto Engine 7. Attestation 8. Audit Trail

Stage 1: Intent Classification

Deterministic pattern matching classifies the inbound request by risk category, domain, and stakes level. No LLM calls -- pure regex and keyword analysis in under 1ms.

Stage 2: Charter Compliance

15 immutable rules and 12 principles evaluated against the classified intent. HARD_BLOCK vetoes terminate the pipeline immediately.

Stage 3: Circuit Breaker

Three-state machine (CLOSED/OPEN/HALF_OPEN) monitors provider health. Open state blocks inference and returns safe degraded responses.

Stage 4: Truth Store

Pre-computed reality layer injects verified facts into the prompt. SHA-256 hashed entries with contradiction detection prevent known-false outputs.

Stage 5: CRD Scoring

Confidence-Reality Divergence metric evaluates output reliability. Domain-specific floors gate assertion levels from ASSERTION to ABSTAIN.

Stage 6: Veto Engine

Pure deterministic veto logic with zero I/O, zero threading, zero global state. Three entry points: check_charter(), check_cognitive_locks(), check_drift_budget().

Stage 7: Attestation

HMAC-SHA256 signed attestation of the governance verdict. Verifiable by any party without EVE AI Core involvement.

Stage 8: Audit Trail

SHA-256 hash-chained JSONL ledger. Every decision, veto, and attestation is appended to an immutable, tamper-evident log.

CRD Scoring (Confidence-Reality Divergence)

CRD is EVE AI Core's core output-quality metric. It measures the gap between how confident an AI output appears and how well it is grounded in verified evidence. High CRD scores indicate fabrication risk.

How CRD Works

  • Evidence-Based Scoring: Each claim in an output is assessed against the Truth Store, Claims Ledger, and source trust levels to produce a grounding score
  • Domain-Specific Floors: Factual domains require 0.9 confidence; creative domains allow 0.4. Thresholds are configurable per deployment
  • Assertion Gating: Outputs below the domain floor are automatically hedged, qualified, or abstained. The system adds qualifiers like "Based on available evidence" rather than asserting uncertain claims
  • Brier Score Calibration: Historical prediction accuracy feeds back into CRD thresholds, tightening floors for domains where the system has been overconfident
Domain Confidence Floor Assertion Level
Factual 0.90 ASSERTION only above floor; ABSTAIN below
Medical / Legal 0.95 ASSERTION with citations; ABSTAIN below
Analytical 0.70 ASSERTION or SPECULATION with qualifiers
Creative 0.40 ASSERTION permitted; creative latitude

Dangerous Content Detection

Pre-inference blocking powered by 210+ compiled regex patterns across 57 attack categories. Dangerous content is intercepted in the Authority Resolution Layer before it reaches the LLM, eliminating the possibility of the model being manipulated into generating prohibited outputs.

Detection Coverage

Patterns are organized into attack categories covering the full spectrum of adversarial techniques and prohibited content types.

  • 210+ Compiled Patterns: Pre-compiled regex for sub-millisecond matching against every inbound request
  • 57 Attack Categories: Prompt injection, jailbreak attempts, identity manipulation, social engineering vectors, harmful content generation, and more
  • Pre-Inference Blocking: Dangerous requests are blocked before any LLM call, not filtered after generation
  • Zero False-Negative Design: Patterns are tuned for recall over precision -- suspicious content is escalated, not silently passed

Prompt Injection Defense

Detects and blocks attempts to override system instructions, inject new personas, or manipulate the governance pipeline through crafted inputs.

Jailbreak Prevention

Identifies multi-turn jailbreak strategies, roleplay-based bypasses, encoding tricks, and instruction-overriding techniques.

Fabricated Terminology Detection

15+ fabricated terms mapped to actual architecture components. Prevents social engineering by enabling substantive corrections rather than generic refusals.

Circuit Breaker

Three-state machine managing LLM provider health with automatic failure detection and recovery. When a provider becomes unreliable, the Circuit Breaker prevents cascading failures by routing traffic to healthy providers or returning safe degraded responses.

CLOSED State

Normal operation. Requests flow to the provider. Failure rate is monitored. Transitions to OPEN when failure threshold is exceeded.

OPEN State

Provider blocked. All requests are redirected to fallback providers or template-based safe responses. No traffic reaches the failed provider.

HALF_OPEN State

Recovery testing. A limited number of probe requests test whether the provider has recovered. Success returns to CLOSED; failure returns to OPEN.

Graceful Degradation

5 degradation levels: NONE (full service), REDUCED (lower quality settings), FALLBACK (backup provider), BROWSER (client-side), TEXT_ONLY (no synthesis).

Fail-Safe Design: The Circuit Breaker defaults to the most restrictive state on ambiguity. Unknown provider states are treated as OPEN until health is verified.

Truth Store

Pre-computed reality layer providing verified facts for prompt injection and post-response validation. Every fact is SHA-256 hashed, timestamped, and sourced. The Truth Store prevents known-false outputs by injecting ground truth into the LLM context and correcting deviations in post-processing.

Architecture

  • SHA-256 Hashed Facts: Each fact entry is content-hashed for integrity verification and deduplication
  • Confidence Decay: Facts lose confidence over time if not re-confirmed, preventing stale information from being treated as current
  • Contradiction Detection: New facts are checked against existing entries. Contradictions are flagged and resolved through source trust weighting
  • Prompt Injection: Relevant facts are injected as [GROUND TRUTH CONTEXT] blocks before LLM generation
  • Post-Response Validation: Outputs are checked against the Truth Store. Corrections are applied at the sentence level using pre-compiled regex patterns

Source Trust Levels

VERIFIED (1.0), AUTHORITATIVE (0.85), RELIABLE (0.70), UNCERTAIN (0.50), UNTRUSTED (0.20). Trust levels weight evidence during conflict resolution.

Audit Trail

Every correction is logged to ground_truth_corrections.jsonl with the original text, corrected text, matched fact, and timestamp.

Charter Enforcement

15 immutable rules and 12 principles form EVE AI Core's constitutional governance layer. Charter rules are evaluated deterministically -- no probabilistic judgment, no LLM interpretation. HARD_BLOCK vetoes cannot be overridden by any user, administrator, or the system itself.

Enforcement Hierarchy

  • HARD_BLOCK: Unoverridable veto. The action is permanently denied. No appeal, no escalation, no administrative bypass. Examples: identity deletion, safety boundary removal, deception about system nature
  • SOFT_BLOCK: Requires explicit justification with audit trail to proceed. The block can be overridden with documented reasoning, but the override itself is logged
  • ESCALATION: Requires human approval before execution. The system pauses and waits for an authorized operator to approve or reject
  • WARNING: Action proceeds but the decision is logged with a concern flag for compliance review

12 Immutable Principles

IDENTITY_INTEGRITY, AUTHENTICITY, NON_HARM, USER_PRIVACY, SAFETY_PRESERVATION, TRANSPARENCY, ACCOUNTABILITY, and more. These cannot be amended or weakened.

15 Concrete Rules

Each principle maps to specific, testable rules with deterministic check functions. No ambiguity in enforcement -- either the rule passes or it does not.

5 Ethical Red Lines

Permanent blocks on impersonation, safety bypass, harmful content generation, deceptive manipulation, and unauthorized data access. These are checked on every request.

Full Audit Trail

Every Charter compliance check -- pass or fail -- is recorded with the action type, parameters, matched rules, veto type, and reasoning.

EU AI Act Alignment: Charter enforcement provides the deterministic safety guarantees required by the EU AI Act (2026). Unlike RLHF-based systems that "usually" comply, EVE AI Core's Charter vetoes are architectural — they cannot be bypassed by creative prompting. EVE AI Core is designed with EU AI Act Article 9 and Article 17 requirements in mind. Independent third-party certification is planned.

AEGIS Automated Red Team

Automated adversarial testing system that continuously probes EVE AI Core's governance infrastructure for weaknesses. AEGIS generates escalating attack patterns, runs them against the TVE pipeline, and reports any governance failures.

Escalating Rigor

Tests begin with known attack patterns and progressively generate novel adversarial inputs. Each round increases complexity and sophistication.

Pattern Generation

Generates multi-turn jailbreak sequences, encoding-based bypasses, roleplay-based exploits, and prompt injection variants targeting each TVE pipeline stage.

Red Team Mode

Defensive security hardening toggle for production: 1.5x risk score multiplier, forced approval on HIGH+ risk, disabled template trust discounts, verbose DEBUG logging.

Validation Campaigns

7-day automated validation proving production readiness. Daily seed rotation, anti-cheat runs every 6 hours, life event injection (10-20/day), and GO/NO-GO verdicts.

Hardware Governance (AIMS)

AIMS (Autonomous Integrity Monitoring System) is EVE AI Core's target hardware design for governance enforcement on Microchip PolarFire SoC FPGA. In that design, veto logic is fused into FPGA fabric so it cannot be modified by software updates, configuration changes, or administrative access. Today the same veto logic runs as a deterministic, side-effect-free software core with a firmware-ready (FPGA-compilable) interface; FPGA deployment is on the roadmap.

Hardware-Fused Enforcement (Target Design)

The Veto Core module (veto_core.py, 1,542 lines) contains ALL pure veto logic from three governance modules in a single side-effect-free module. Zero imports outside dataclasses, enum, typing. Zero I/O, zero threading, zero global state. This module is designed for direct compilation to firmware.

  • PolarFire SoC: Microchip PolarFire SoC with RISC-V processor and FPGA fabric. AIMS register maps defined in 5 hardened appendices
  • Physical Isolation (roadmap): In the target hardware design, veto logic runs on dedicated FPGA fabric, physically isolated from the application processor, so no software path can bypass it. Today the veto runs as a deterministic, side-effect-free software core with a firmware-ready interface
  • C Header Contract: veto_interface.h (401 lines) defines the firmware API contract for hardware implementation
  • Frozen Constants: 15 CHARTER_RULES, 5 ETHICAL_RED_LINES, 13 PROTECTED_INVARIANTS, 6 LOCK_THRESHOLDS -- all frozen at synthesis time

Pure Deterministic Module

Three pure entry points: check_charter(), check_cognitive_locks(), check_drift_budget(). No side effects. Identical output for identical input, always.

87 Verification Tests

Test suite covering determinism (same input = same output), equivalence (software matches hardware contract), and purity (no hidden state mutations).

Sovereign SDK

Governance-as-a-service for enterprise customers. The Sovereign SDK exposes EVE AI Core's governance infrastructure as tenant-isolated REST APIs with Python and JavaScript client libraries.

Tenant Isolation

Each organization receives its own isolated governance instances. No cross-tenant data leakage is architecturally possible.

  • Per-Org Instances: Isolated Charter, Claims Ledger, Trust Dial, Action Registry, and Reality Anchor per organization
  • Immutable Base: 12 charter principles are shared read-only. Custom rules can only ADD restrictions, never weaken the base
  • API-Key Authentication: Scoped API keys with sovereign permission level
  • 30 REST Endpoints: Full governance API at /api/sovereign/
  • 21 Webhook Events: Real-time governance notifications for charter vetoes, claim resolutions, trust evaluations, and action approvals

Python SDK

evecore -- Full sovereign governance client for Python applications. Charter checks, claim registration, trust evaluation, and action proposals.

JavaScript SDK

Call the governance REST API directly from Node.js, the browser, or any language -- no SDK install required.

Custom Charter Rules

Organizations can add custom rules scoped to their compliance requirements. Custom rules can only tighten restrictions -- they cannot weaken the immutable base.

Usage Metering

Sovereign API calls are metered per billing period. Free: 0, Pro: 10K, Team: 5K, Enterprise: unlimited.

Resilience Score Engine

Unified composite metric (0-100) measuring EVE AI Core's structural integrity. The Resilience Score aggregates four governance sub-layers into a single auditable number that operators and compliance teams can use to assess system health at a glance.

Scoring Formula

Score = 0.30 * Governance + 0.25 * Identity + 0.25 * Behavioral + 0.20 * System

  • Governance Layer (30%): Charter compliance rate, veto accuracy, audit chain integrity
  • Identity Layer (25%): Drift budget consumption, invariant verification, anchor stability
  • Behavioral Layer (25%): Output consistency, CRD calibration, pattern adherence
  • System Layer (20%): Provider health, Circuit Breaker state, resource utilization
Health Level Score Range Meaning
EXCELLENT 90-100 All governance layers operating at full capacity
GOOD 70-89 Minor degradation in one or more layers
FAIR 50-69 Significant degradation requiring attention
POOR 30-49 Critical degradation; remediation required
CRITICAL 0-29 Governance integrity compromised; automatic lockdown

Cryptographic Audit Trail

Every governance decision produces a tamper-evident record. The audit trail uses SHA-256 hash-chaining and HMAC-SHA256 attestation signing to create an immutable evidence chain that can be independently verified by auditors, regulators, and compliance teams.

SHA-256 Hash Chain

Each audit entry includes the SHA-256 hash of the previous entry, creating a chain where any tampering is immediately detectable by hash verification.

HMAC-SHA256 Attestations

Governance verdicts are signed with HMAC-SHA256 using JWT_SECRET_KEY. Signatures can be verified without access to EVE AI Core's infrastructure.

Resilience Certificates

On-demand cryptographically signed certificates attesting to current governance integrity. Auditors verify via the /api/resilience/certificate/verify endpoint.

7+ Year Retention

Immutable ledger records retained for 7+ years to meet financial services and healthcare compliance requirements (SOX, HIPAA, GDPR).

Independent Verification: Any party with an attestation can verify its authenticity against the public verification endpoint without requiring access credentials or EVE AI Core infrastructure.

Security & Authentication

Enterprise-grade security controls protecting the governance infrastructure and operator access.

YubiKey / FIDO2 Hardware Key Authentication

Critical governance operations are gated by physical hardware security key authentication using the WebAuthn/FIDO2 standard. FIPS 140-2 Level 2 certified protection for the most sensitive operations.

  • 14 Protected Operations: Privileged Operator Mode (6 operations), Emergency Controls, Registry Mode, Charter Override, Configuration-Change Approval, Capability Requests, Adversarial Test Mode
  • No Fallback: If YubiKey authentication fails, the operation is denied. Physical presence is required by design
  • Proof Token Bridge: 60-second JWT proof tokens with replay prevention bridge the dual-server architecture

JWT Authentication

Stateless session tokens with configurable expiry, role-based access control, and per-endpoint permission enforcement.

RBAC System

5 roles (Viewer, Operator, Approver, Admin, Platform Admin) with 9 granular permissions and tenant isolation.

Rate Limiting

Token bucket algorithm prevents brute force attacks. Per-user, per-IP, and global rate limits with configurable windows.

Operator Audit Logging

JSONL persistence of all operator actions: cancel, retry, approve, reject, export, red-team-toggle. Includes actor, tenant, roles, timestamp, and reason.

Weighted Risk Assessment Engine

Pattern-based risk scoring for command and action evaluation. The risk engine assigns weighted scores based on command patterns, scope, and autonomy mode to determine whether human approval is required.

Weighted Scoring

Pattern weights by severity: CRITICAL (1.5x), HIGH (1.2x), MEDIUM (1.0x). Scope-based factors: SECRETS_ACCESS (20), PRIVILEGED_OPS (18), SHELL_LIMITED (12).

Autonomy Multipliers

Risk scores scaled by operating mode: AUTONOMOUS (1.3x), ASSISTED (1.0x), MANUAL (0.8x). Higher autonomy requires stricter governance.

Risk Levels

LOW (0-24): auto-approve. MEDIUM (25-49): log and proceed. HIGH (50-74): require approval. CRITICAL (75+): block and escalate.

Tiered Action Policy

4 tiers: AUTO_EXECUTE (observation, internal), AUTO_EXECUTE_WITH_LOG (memory, search), REQUIRES_CONFIRMATION (communication, API), BLOCKED (system control).

Ready to Deploy Deterministic AI Governance?

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Feature Availability by Tier

Feature Pro Team Enterprise
Three-Layer Trust Infrastructure Yes Yes Yes
TVE 8-Stage Pipeline Yes Yes Yes
CRD Scoring Yes Yes Yes
Dangerous Content Detection Yes Yes Yes
Circuit Breaker Yes Yes Yes
Truth Store Yes Yes Yes
Charter Enforcement Yes Yes Yes
Cryptographic Audit Trail 30 days 1 year 7+ years
AEGIS Red Team - Yes Yes
Resilience Score + Certificates - Yes Yes
Sovereign SDK 10K calls/mo 5K calls/mo Unlimited
Hardware Governance (AIMS) - - Yes
YubiKey / FIDO2 Authentication - Yes Yes
Weighted Risk Engine Yes Yes Yes
Operator Console - Yes Yes
Custom Charter Rules - - Yes
Part of the EVE AI Core control plane Deterministic AI Governance Control Plane → Policy decisions that return the same result for the same input every time, before execution.