GDNGlobal Decision Network
Case studies OC Labs

Independent engineering assurance

GDNGlobal Decision Network

AI can generate engineering work. GDN determines whether that work should be trusted.

Independent verification, machine evidence, repair-before-acceptance, and auditable engineering outcomes.

Explore verification View evidence
Engineering outcomeVERIFIEDMaterial requirements satisfied
Objective
Solution
Verification
Evidence

The problem

Plausible is not the same as correct.

AI-generated engineering can look complete and pass ordinary checks while still failing the requirement that actually matters. Confidence and agreement are not substitutes for evidence.

How GDN works

A clear path from objective to decision.

  1. 01Objective

    Define the result and the requirements that matter.

  2. 02Solution

    Assess the proposed engineering work as a claim to be tested.

  3. 03Independent Verification

    Challenge the solution separately from its creator.

  4. 04Evidence

    Use observable checks to establish what is supported.

  5. 05Decision

    Accept, repair, reject, or stop when evidence is insufficient.

Assurance

Verification cannot simply agree with itself.

GDN only accepts an outcome when the requirements that actually matter have been explicitly verified.

VERIFIED

Material requirements are supported by evidence.

CHALLENGE FOUND

An independent finding needs resolution.

REPAIR REQUIRED

A bounded correction is needed before acceptance.

INSUFFICIENT EVIDENCE

The available evidence cannot support a conclusion.

Evidence

Simple decision. Deep evidence.

A concise outcome on the surface, with the supporting trail available underneath.

Engineering outcome VERIFIED
Material requirements
6 / 6
Independent verification
Passed
Regression checks
Passed
Evidence integrity
Verified
Remaining uncertainty
Documented

Verified case

When both engineers made the same mistake

Independent verification found what the first solution missed.

  1. 01

    Problem

    A real public TypeScript generic-propagation case in unjs/ofetch.

  2. 02

    Baseline

    A plausible repair passed repository typechecking, but failed the frozen harness with five diagnostics.

  3. 03

    GDN Creator

    The Creator independently produced the same incorrect abstraction.

  4. 04

    Independent Verification

    The verifier detected the unresolved defect and triggered the permitted bounded repair.

  5. 05

    Verified Outcome

    The repaired GDN candidate was the only patch to pass the frozen acceptance requirements.

Result summary

Classification
GDN WIN — single controlled case
Baseline
FAIL
GDN
PASS
Verifier contribution
Detected a shared incorrect abstraction and triggered the successful bounded repair.

This is a single controlled engineering case. It does not establish general GDN superiority or constitute production or security certification.

Inspect the published evidence

Demonstrated behavior

The evidence decides the outcome.

Across real public engineering tasks, GDN has repeatedly demonstrated a substantial practical advantage in speed and verification—producing tested, reviewable outcomes in unusually short timeframes.

GDN's controlled engineering work has produced a mix of wins, ties, inconclusive results, verifier interventions, and cases where both approaches failed.

GDN does not require itself to win. It fails closed when evidence does not support a conclusion.

Bounded pilot

Give GDN one problem.

Provide one bounded, non-sensitive engineering problem or AI-generated change.

GDN returns:

  • Engineering outcome
  • Verifier findings
  • Material requirement status
  • Repair history where required
  • Machine evidence
  • Regression evidence
  • Provenance
  • Remaining uncertainty
Discuss a GDN pilot