Every model call, agent step, and tool invocation, signed into one tamper-evident audit chain, with a plain-English account of each decision for the people who answer for it.
Sample production view · auditor view · synthetic data
Select your perspective to see how Hyperaxis solves your specific accountability challenges.
Regulators require proof, not promises. Hyperaxis gives you the empirical evidence to demonstrate that your organisation's AI systems are governed, compliant, and continuously monitored.
Captures the full agentic surface. Direct model calls, multi-step chains, MCP tool invocations, and agent-to-agent traffic all sign onto the same audit chain. Works with any language and any framework. No SDK rewrites required.
Every decision produced by an AI system is assigned a unique DRI. This acts as the backbone for accountability, threading raw inputs, model weights, and final outputs into a cohesive, auditable ledger.
A complete operational framework ensuring every AI interaction is logged, verified, and traceable. Built to withstand intense regulatory scrutiny.
AI decisions are logged flawlessly at the precise point of interaction. We capture exactly what was prompted, the model state, and the unaltered response.
Raw JSON logs do not hold up in court, nor do they satisfy stakeholders. Our proprietary narrative engine translates technical evidence into plain-English (and German) explanations, instantly exportable as pristine PDF reports.
The architecture, the threat model, and the regulator-readiness assumptions are not internal claims. They are stated, dated, and citable. Four papers in the Series are deposited with DOIs; a fifth on cryptographic audit primitives is in draft for June 2026.
Why governance-by-process fails when the artefact under audit is a non-deterministic model, and what a cryptographic provenance layer must do instead.
A SHA-256 hash chain with per-entry Ed25519 signatures, dual-path timestamping, and the verification protocol that a regulator can run unaided.
Why most AI governance tooling fails to ship in regulated industries, and what the procurement-officer test reveals about the missing layer.
How an evidence-grade audit trail changes the dispute-resolution model for AI-assisted trading and credit decisions.
We treat digital evidence with the same gravity as embossed, sealed physical documents. Hyperaxis ensures your AI operations are recorded with irreversible permanence.
Read our methodology
Generic AI gateways move tokens. Model evaluators score outputs. In-house audit logs accumulate. Only Hyperaxis produces an artefact a regulator can verify without engineering assistance.
| Capability | Generic AI gateway | Model evaluator | In-house audit log | Hyperaxis |
|---|---|---|---|---|
| Cryptographic chain of custody | ○ token logs only | ○ evaluator output only | ○ mutable database row | ● SHA-256, Ed25519, dual-anchored |
| Plain-English narrative at write-time | ○ none | ○ none | ○ drafted at audit-time | ● generated alongside the chain entry |
| Regulation mapping | ○ none | ○ model-card focus | ○ bespoke | ● EU AI Act, FCA, NHS DSPT, ISO 42001, SOC 2 |
| Public third-party verification | ○ internal only | ○ not applicable | ○ not externally verifiable | ● verify.hyperaxis.co.uk, no system access required |
| Open primitive on PyPI | ○ proprietary | ○ mostly proprietary | ○ not packaged | ● Nexuscone, installable, auditable |
Whether you audit, advise, or comply. Hyperaxis gives you the evidence infrastructure to act with certainty.
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