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
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).
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.
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
sovereignpermission 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).
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?
Schedule a technical assessment to evaluate EVE AI Core for your compliance requirements.
Schedule AssessmentFeature 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 |