The Problem We Solve
Enterprise AI adoption has stalled at the compliance boundary. Organizations deploying large language models face three unsolved infrastructure gaps: hallucination liability (no forensic evidence of what went wrong), jailbreak exposure (software-only safety is routinely bypassed), and regulatory uncertainty (no deterministic proof that governance was enforced for any specific decision).
EVE CoreGuard is the deterministic governance enforcement layer that intercepts and vetoes AI actions before they reach production. EVE Proof is the certification infrastructure that records every decision as a signed, verifiable receipt your audit team can check independently — even years later. Together, EVE AI Core lets regulated teams govern AI actions before execution and preserve signed, independently verifiable evidence for audit, replay, and procurement review.
What We Build
EVE AI Core is not a filter, wrapper, or guardrail. It is infrastructure — a deterministic AI trust infrastructure that resolves authority on AI actions at the architectural level. The same veto logic that runs on a server is designed to compile to FPGA firmware (a roadmap target).
Deterministic Veto Core
15 immutable charter rules and 5 ethical red lines evaluated in sub-millisecond time. Pure deterministic functions with zero I/O — compilable to FPGA firmware. Pillar 128 Hard-Fail-Shut: enforcement errors default to veto, never fall-through.
Three-Layer Trust Infrastructure
Physical isolation of authority resolution (Authority Resolution Layer), AI inference (Governed Inference Layer), and authority records (Cryptographic Authority Chain Layer). No signal path exists from Execution to Control.
Sidecar Forward Proxy
Non-bypassable egress interception on port 3128. Set HTTPS_PROXY and every outbound request transits EVE. On veto: TCP connection severed, signed Decision Certificate emitted. The model's internal alignment state is irrelevant.
CRD Scoring Engine
Confidence-Reality Divergence measures the gap between what AI claims and what evidence supports. Domain-aware thresholds for financial, medical, legal, and safety contexts.
Cryptographic Audit Trail
Every governance decision is Ed25519-signed, hash-chain linked, and mapped to EU AI Act, NIST AI RMF, and ISO 42001 requirements. Offline verification — auditors verify with the published public key, without calling EVE.
Abliteration Defense
In our internal OBLITERATUS adversarial test suite (512 prompts across 7 severity tiers), architectural enforcement catches harmful content from models with no internal safety — the regex layer alone blocked 34.8%, and every evaluated request produced a signed decision certificate.
Our Principles
Determinism Over Probability
We don't filter or classify — we enforce. Same input, same policy version, same governance decision. No probabilistic safety, no statistical guardrails.
Hardware-Level Enforcement (Roadmap)
In the target hardware design, governance logic runs in FPGA fabric, separate from the model — so inference has no path to alter its own governance. Today that boundary is enforced by the deterministic software veto core; the FPGA reference design is on the roadmap.
Audit-Grade Provenance
Every decision is signed, timestamped, and chain-linked. The audit trail cannot be altered without detection. Regulators can verify independently.
Continuous Adversarial Hardening
Our AEGIS system uses AI to attack our own governance 24/7, automatically generating and patching detection patterns. Adversarial coverage is continuously expanded.
The AIMS Architecture
AI Integrity Management System
AIMS is the hardware-software governance stack designed to make EVE AI Core's enforcement boundary non-bypassable. It targets the patented Three-Layer Trust Infrastructure on Microchip PolarFire SoC (RISC-V + FPGA), so that governance logic is physically isolated from AI execution. Today that boundary is enforced by the deterministic software veto core — which has no signal path from the Governed Inference Layer back to the Authority Resolution Layer — with FPGA deployment on the roadmap.
Authority Resolution Layer
Pre-inference governance: intent classification, charter veto, circuit breaker, drift budget, policy mesh. All decisions made before the AI sees the request.
Governed Inference Layer
Runtime AI operations: LLM routing, agent orchestration, and other governed runtime services. Governed by Authority Resolution Layer policies but cannot modify them.
Cryptographic Authority Chain Layer
Post-inference verification: TVE pipeline, CRD scoring, attestation certificates, forensic reconstruction, adversarial resilience.
Founder
Jamaurice Devron Holt
Founder & CEO, EVE NeuroSystems LLC
EVE CoreGuard was not designed by a research lab or a committee. It was architected and built, end to end, by one person who spent roughly two decades keeping the data systems of large enterprises correct, available, and accountable — and who concluded that AI governance is, fundamentally, an infrastructure problem, not a model-tuning problem.
Jamaurice Holt has spent close to twenty years in enterprise data infrastructure, including database administration for Fortune-class enterprise systems — the kind of environments where a single unaccounted-for write, an unprovable change, or a missing audit record is not an inconvenience but a regulatory and financial liability. That background shaped a specific conviction: in regulated systems, the question is never just “was the answer good?” — it is “can you prove, deterministically and after the fact, exactly what was enforced and why?”
That conviction is the credibility bridge to EVE's entire thesis. Probabilistic guardrails and software filters fail the enterprise data-discipline test for the same reason an unlogged production change does: they cannot be replayed, cannot be independently verified, and cannot survive an examiner who asks for evidence at the moment of the decision. EVE's answer — deterministic enforcement that produces the same verdict for the same input every time, paired with cryptographically signed, offline-verifiable decision evidence — is the natural translation of decades of database-administration and audit-trail discipline into the AI layer.
~20 Years in Data Infrastructure
Enterprise data infrastructure and database administration for Fortune-class systems, where provable correctness and audit trails are non-negotiable.
Sole Architect & Builder
EVE CoreGuard — from the deterministic FPGA-compilable veto core to the automated adversarial hardening — was built personally, not assembled by a vendor stack.
90 U.S. Provisional Patent Applications
Filed as sole inventor across the full AIMS stack. Single-owner IP with no fragmentation; serial numbers are public at the USPTO.
AI Systems Architect
Designs the hardware-software trust boundary so AI inference is isolated from the authority that governs it.
The result is a deliberately undiluted point of view. Because EVE CoreGuard has a single architect and a single owner of its intellectual property, the system's governance model is internally consistent end to end — the veto logic, the evidence chain, and the compliance mapping all express one coherent thesis rather than the compromises of a fragmented design. For an enterprise buyer evaluating who is behind their AI governance layer, that means a clear line of accountability and a builder whose entire career has been about making systems answerable.
Choose Your Path
License EVE CoreGuard for enterprise deployment, certify every decision with EVE Proof, deploy the sidecar for mandatory governance, or use the hosted platform.