Digital HumanRESEARCH / NEUROLOGIC AI

The thinking behind
the intelligence.

Research frameworks, a filed method, and the technical work behind Digital Human. Drafts and evaluation packs are available to qualified partners under NDA.

Explore the research

THE METHOD, OPEN TO EXAMINATION

NEUROLOGIC AITECHNICAL PAPER

The Digital
Human Model

Architecture & evaluation

Approved
learning materialSeparate
held-out test

Available to qualified partners under NDA

Frameworks / in preparationMethod / patent filed 2026

Research frameworks · technical paper · filed method

A METHOD YOU CAN EXAMINE

Follow the method. Then examine the evidence.

The connection between observed work and a measured outcome should be inspectable.

Observe decisions in context.

A useful trace preserves the starting state, the decision, any correction and the result. That is the material the specialist learns from.

Consented demonstrations · architecture

HOW THE EVIDENCE IS BUILT

Start with inspectable work.

LEARNING MATERIALApproved
demonstrations

Context · decision · outcome

Separate sets

EVALUATION MATERIALHeld-out
tasks

Defined success · recorded errors

REPORTING CHECKLIST

What was tested
What the comparison used
What passed—and what did not
Where the claim stops

Evaluation design principle. The engineering study uses held-out circuits; each published evaluation states its own method.

Keep the test outside the lesson.

Held-out tasks remain separate from training. Define success before evaluation and report errors alongside the measured result.

Evaluation design principle · held-out engineering circuits

HOW THE EVIDENCE IS BUILT

Keep the test separate.

LEARNING MATERIALApproved
demonstrations

Context · decision · outcome

Separate sets

EVALUATION MATERIALHeld-out
tasks

Defined success · recorded errors

REPORTING CHECKLIST

What was tested
What the comparison used
What passed—and what did not
Where the claim stops

Evaluation design principle. The engineering study uses held-out circuits; each published evaluation states its own method.

Keep the method open to scrutiny.

Dated methods, prompts, judgments and limitations support the reported comparisons. Qualified teams can inspect the underlying packs with our model team.

Internal evidence · independent review remains a next step

HOW THE EVIDENCE IS BUILT

Report the result with its limits.

LEARNING MATERIALApproved
demonstrations

Context · decision · outcome

Separate sets

EVALUATION MATERIALHeld-out
tasks

Defined success · recorded errors

REPORTING CHECKLIST

What was tested
What the comparison used
What passed—and what did not
Where the claim stops

Evaluation design principle. The engineering study uses held-out circuits; each published evaluation states its own method.

HOW THE EVIDENCE IS BUILT

Start with inspectable work.

LEARNING MATERIALApproved
demonstrations

Context · decision · outcome

Separate sets

EVALUATION MATERIALHeld-out
tasks

Defined success · recorded errors

REPORTING CHECKLIST

What was tested
What the comparison used
What passed—and what did not
Where the claim stops

Evaluation design principle. The engineering study uses held-out circuits; each published evaluation states its own method.

Consented demonstrations · architecture

PAPERS & TECHNICAL WRITING

The method, written down.

Research status stays attached to each item. A draft is not a published paper.

RESEARCH FRAMEWORK

Execution-based SOP validation

Evaluating documented procedures against observed execution, and identifying the gaps that make automation fail.

Preprint in preparationDiscuss this research

RESEARCH FRAMEWORK

Reinforcement learning for workflow cloning

Expert-weighted synthesis, compliance-first rewards, verified outcomes, and recovery learned from real work.

Preprint in preparationDiscuss this research

TECHNICAL WHITE PAPER

The Digital Human Model: architecture and evaluation

The compact multimodal model, training inside the customer boundary, evaluation methods, and the role of abstention.

Available under NDARequest access

FILED METHOD

Capture-and-train, and expert-weighted synthesis

Consented capture and compliant expert demonstrations as the foundation for a specialist model. International filings are in progress.

Patent filed · 2026Explore the method

PERSPECTIVES

A different way to think about work.

RESEARCH NOTE

TECHNICAL DILIGENCE

Bring your hardest questions.

Review the model architecture, evaluation methods, and deployment approach with the people building them.

Discuss the research Request the white paper

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The thinking behind
the intelligence.

Follow the method. Then examine the evidence.

Observe decisions in context.

Start with inspectable work.

Keep the test outside the lesson.

Keep the test separate.

Keep the method open to scrutiny.

Report the result with its limits.

Start with inspectable work.

The method, written down.

Execution-based SOP validation

Reinforcement learning for workflow cloning

The Digital Human Model: architecture and evaluation

Capture-and-train, and expert-weighted synthesis

A different way to think about work.

The averaging fallacy

From experiment to scale

Polanyi and the last automation frontier

Bring your hardest questions.

The thinking behindthe intelligence.

Follow the method. Then examine the evidence.

Observe decisions in context.

Start with inspectable work.

Keep the test outside the lesson.

Keep the test separate.

Keep the method open to scrutiny.

Report the result with its limits.

Start with inspectable work.

The method, written down.

Execution-based SOP validation

Reinforcement learning for workflow cloning

The Digital Human Model: architecture and evaluation

Capture-and-train, and expert-weighted synthesis

A different way to think about work.

The averaging fallacy

From experiment to scale

Polanyi and the last automation frontier

Bring your hardest questions.

The thinking behind
the intelligence.