EVE AI Core
The Infrastructure of No.
EVE sits above the AI stack you already run — OpenAI, Claude, Bedrock, Azure, LangChain, LlamaIndex, your identity, security, and data platforms — and turns every governed decision into a signed record you can verify independently. You don't buy another model. You buy the control plane that governs all of them.
You control which decision fields are sent; in VPC and on-prem deployments, governed content and evidence stay inside your boundary. With EU AI Act GPAI-model obligations applicable since 2 August 2025 and high-risk-system obligations phasing in from 2 December 2027 (Annex III) and 2 August 2028 (Annex I) under Regulation (EU) 2026/1744, and with SR 26-2 (the April 2026 interagency model-risk guidance that superseded SR 11-7, applied primarily to banking organizations above $30B in total consolidated assets) excluding generative and agentic AI from its formal scope while still expecting such technologies to be governed, the record has to exist at the moment of the decision. Trust Center · Security
Framework mappings describe technical control support and evidence capabilities. They do not constitute legal advice, regulatory certification, or a guarantee that a customer’s deployment is compliant. “SOC 2 Type II — In Progress” means an independent SOC 2 Type II audit is engaged (Decrypt CPA, via Scytale) and the observation period is underway; it is not a completed audit or an issued attestation.
One closed loop runs over every model invocation and agent step — and the same signed evidence travels with it from policy kernel to independent auditor.
Route any model invocation or agent step through EVE's deterministic policy kernel.
EVE CoreGuard →On the hosted service, auditors verify any record against the published ECDSA P-384 public key — independent, no EVE account. Self-hosted evecore records use a customer-held HMAC-SHA256 shared key for local integrity checks.
Run it in SaaS, your VPC, private cloud, or fully on-prem. Consistent evidence schema across deployment models — signing architecture appropriate to each deployment.
Deployment →Most AI governance platforms focus on visibility, dashboards, policy mapping, model inventory, and compliance workflows. EVE AI Core is designed as a deterministic enforcement and proof layer.
Visibility and workflow. Dashboards, model inventory, policy mapping, risk registers, and audit-ready reporting. Essential layers — but they observe and document AI systems. They don't stand between an AI system and its next action.
Enforcement and proof. Before an AI system, application, or agent takes action, EVE evaluates the proposed action against policy and returns an ALLOW, MODIFY, or BLOCK decision — deterministically. Afterward, EVE produces signed evidence that can be audited, verified offline, and replayed.
This makes EVE complementary to enterprise GRC and AI governance platforms, while providing a stronger runtime control layer for high-risk AI operations.
EVE AI Core is the deterministic runtime enforcement and cryptographic evidence layer for enterprise AI governance.
EVE plugs into the tools your teams already use and becomes the governance and evidence layer across all of them — instead of asking you to replace anything.
All product names, logos and brands are the property of their respective owners and are used here for identification only. Their use does not imply affiliation with, sponsorship by, or endorsement from those owners. Connector capability varies by platform — see the connector-readiness matrix for what each integration does and does not do.
Governance is only worth anything if it holds when it is inconvenient. These are the invariants the rest of this page rests on — the properties that stay true whichever model, framework, or cloud you put underneath.
Every verdict comes from a deterministic policy kernel. No language model sits anywhere in a decision path, so the same input yields the same verdict — today, and on replay a year from now in front of an examiner.
In enforce mode a BLOCK is decided ahead of the downstream connector, so the blocked action is never carried out. Detection after execution is a report. Refusal before execution is a control.
What the policy decided is one record. What the system then actually did is another. Keeping them apart is what lets an auditor tell an approved action from a completed one — and stops either being quietly restated as the other.
If a policy, a signing key, or an evidence store is unreachable on the decision path, the answer is refusal — not a pass-through. An outage in the governance layer degrades throughput, never the control.
A signed decision record re-hashes and re-verifies offline, with no EVE service in the loop and no account with us required. A vendor you have to trust to check the vendor is not evidence.
Imported policies and proposed remediations land as drafts. Enforcement modes are set by an operator, not inferred. A system that can widen its own authority is not a control plane.
Each of these is a property you can test rather than take on faith — start with a record and check it yourself. Verify a signed decision →
The differentiator isn't that EVE watches your AI — it's that every decision is a signed, verifiable, replayable artifact your controls team and your regulator can validate independently.
A single signed record — re-hashable and re-verifiable offline, without an EVE service.
A live governance coverage view across every connected system — the number auditors, CISOs, and regulators understand instantly.
Six layers, six questions. Every enterprise AI governance program has to answer all of them — EVE goes deepest where the stakes are highest.
EVE AI Core focuses on the enforcement, evidence, and replay layers while supporting inventory, policy, workflow, risk, and compliance mapping across the rest of the stack.
Paste a sample record into the verifier, then change one character and watch the proof break.