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Capabilities

The full function
scope

PREEXEC is a deterministic pre-execution governance engine. Every input is evaluated and given a verdict — EXECUTE, HOLD or BLOCK — before your AI acts on it. This is what the engine actually does, end to end.

How the verdict is reached

For each input PREEXEC computes a ClarityScore from three intrinsic clarity signals; the fourth signal — alignment with your own policy — acts as an independent policy gate, not as part of the score. It measures clarity, not meaning or truth: a clearly written but nonsensical instruction scores as high-clarity. That restriction is exactly what makes the engine deterministic.

ssynt

syntactic well-formedness

ssem

semantic unambiguousness

saff

clarity of affect / intent

spol

alignment with your policy

The three clarity signals combine into a single ClarityScore. An input is released only when it clears the clarity thresholds you configure and passes the policy gate: policy conflicts surface as a red or yellow gate result with per-rule severity — independent of how clearly the input is written. Below the thresholds an input is held for review or blocked. There is no second scoring axis: clarity thresholds plus the policy gate decide.

What the engine does

The clarity gate is the headline, but it sits on a full governance platform — every area below is a live, addressable part of the engine.

01Evaluation

Single, batch and pairwise pre-execution verdicts — and simulate a policy change before it goes live.

02Policy lifecycle

Author your own policy with the Policy Generator; version, import and restore; evaluate it against your own corpus.

03Calibration & auto-tuning

Versioned, SHA-256-tagged calibration bundles; per-policy auto-tuning of thresholds.

04Tamper-evident audit

Merkle-hashed chain, ECDSA-P-256 signing, RFC-3161 TSA anchoring; forensic search, export and integrity checks.

05Clarity guidance

On a HOLD, the engine returns categorised follow-up questions (vague / missing / deictic / generic) to sharpen the input.

06Ontology & knowledge graph

A clarity ontology behind the semantic signal, plus a knowledge graph with risk propagation across entities.

07Human review

Adjudication queue, delegations and arbitration for the cases that need a person in the loop.

08Incidents & predictive

Incident declaration, predictive signals and insider-threat / agent-integrity monitoring.

09Governance & RBAC

Role- and permission-based access, plus Layer-0 meta-policy conflict resolution across competing policies.

10Data lineage & DPR

Entity-level data lineage and data-protection-request handling, supported by design.

11Integrations

OpenAI-compatible proxy (drop-in), 22 LLM provider adapters, SIEM forwarding, webhooks and OIDC SSO.

12Compliance maps

Control mappings for EU AI Act, ISO 27001, ISO 42001, SOC 2, NIST AI RMF and NIS2.

Three properties that define it

Deterministic. The same input under the same calibration bundle always produces exactly the same verdict — reproducible and defensible.

On-premise & air-gapped. The engine runs inside your environment; the ML models ship bundled in the image; no requests leave the deployment boundary.

Tamper-evident. Every decision is written to a cryptographically chained, operator-bound audit trail that can be exported and independently verified.

By the numbers

Our own measurements

Measured on release 4.7.0 — full corpus re-runs, July 2026

Note on use

PREEXEC™ is a deterministic measurement tool for evaluating AI inputs and outputs. It does not make autonomous decisions about persons, matters, or legal consequences. Verdicts (EXECUTE / HOLD / BLOCK) are technical classifications based on configured thresholds; operational and legal responsibility for decisions made using these classifications rests entirely with the system operator. Compliance reports, audit trails, and reproducibility evidence are documentation aids and do not replace qualified compliance assessment.

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