Ukonmieli PCT/FI2026/050579 · Patent pending

Strategic briefing · Industrial AI

Can industrial AI leaders afford to build the next generation of industrial AI without an independently verifiable governance and trust layer?

The next competitive phase of industrial AI will not be decided solely by who builds the most capable models. It will be decided by who can prove that AI-driven decisions are governed, verified, traceable, and trustworthy — before they influence industrial operations.

Request an NDA briefing See the approach

The problem

Industrial AI is moving from recommendations to autonomous operations

Industrial operators already use AI for analysis, optimization suggestions, and decision support. The next step — AI that can directly influence process settings, control loops, and operational workflows — raises a governance question that model capability alone cannot answer.

Before an AI workload enters an operational environment, how do you independently verify its integrity, authorization, provenance, and governance? Without a verifiable trust layer, autonomy becomes a liability: customers, regulators, and operators will demand evidence that every AI-driven action was authorized, unchanged, and accountable.

Engineering excellence in the industries of the future depends not only on smarter models, but on sustainable, partnership-ready solutions that keep AI under verifiable control as autonomy grows.

Waiting until verifiable governance becomes a standard customer requirement means catching up — not defining the direction.
  • PassionSerious about trustworthy industrial AI at scale
  • PartnershipBuilt for collaboration under clear NDA terms
  • PerspectiveGovernance as competitive advantage, not afterthought
  • VersatilityDesigned to complement platforms such as Metris

The approach

A deterministic trust layer for industrial AI workloads

PCT/FI2026/050579 describes an architecture for governing AI workloads so that decisions can be verified, locked on deviation, and sealed as evidence — without collecting personal data and with explicit data-sovereignty controls. It is designed to complement industrial AI and IIoT platforms such as Metris, adding an independently verifiable governance layer rather than replacing existing automation stacks.

  • Deterministic canonicalization & fingerprinting

    Every workload is normalized and bound to a cryptographic fingerprint, so identical intent produces identical evidence.

  • L1–L4 multi-layer governance

    Routing, cryptography, data sovereignty, and license/WORM controls are separated into distinct lines of responsibility.

  • Automated AUDIT_LOCK

    On deviation, execution enters a sealed audit state automatically — evidence is preserved before further operational influence.

  • Cryptographic evidence & WORM logging

    Audit trails are sealed for write-once retention so post-incident reconstruction remains tamper-evident.

  • RFC 3161 trusted timestamping

    Execution logs can be cryptographically bound to an independent trusted timestamp authority.

  • Data sovereignty & zero retention

    Governance is designed so integrity can be proven without unnecessary retention of sensitive operational content.

  • Distributed architecture & Master Integrity Key

    A 16-node cluster model with a Master Integrity Key ties configuration integrity to fail-safe interruption on unauthorized change.

High-level governance flow

Status

What exists today

PCT application pending

PCT/FI2026/050579 is a pending international patent application. No granted patent rights are claimed on this page.

Working reference implementation

A software reference implementation covering the claim structure exists for controlled technical evaluation — not published here.

Technical material under NDA only

Architecture detail, source material, and evaluation packages are shared only after a written NDA and scoped evaluation agreement.

Engagement model

A controlled path from evaluation to partnership

  1. 01

    Strategic evaluation under NDA

    Assess claim relevance and integration potential for industrial AI platforms — without transferring broad license rights or implementation source.

  2. 02

    Scoped proof-of-concept

    Run a bounded PoC in an industrial simulation environment for one agreed use case before any production commitment.

  3. 03

    Licensing or strategic partnership

    Negotiate commercial terms after evaluation — licensing, collaboration, or a broader strategic arrangement as appropriate.

Evaluation access does not include exclusivity, broad use rights, or free delivery of the full technical implementation package.

Request an NDA briefing

Serious discussions with teams responsible for digitalization, industrial AI strategy, automation platforms, and technology partnerships are welcome. The first step is a confidential briefing under NDA.

Request an NDA briefing

Email: ukonmieli@gmail.com