01
Identify the object
Intake, custody, and SHA-256 identity before anyone argues about a result.
SYS // LAB-03 · WY · CHEYENNE
AI-Native Testing. Human-Verified Results.
An AI-native laboratory operating system is in development. This public site is the institutional front door — not a product storefront, not a chatbot, and not a live certification service.
Technical Testing for the Technologies of Tomorrow. Engineering Confidence Through Evidence. A scientific testing and compliance laboratory in development.
Lab OS · in development
ETTC is building an AI-native laboratory operating system: intake, evidence identity, assisted analysis, human verification, report control. This website is the public front door to that work.
Locked public facts
Next generation
Software, models, interactive systems, payments evidence, and integrity controls are engineering objects. ETTC treats them as such: identified, hashed, tested, and reported with limitations in view.
01
Intake, custody, and SHA-256 identity before anyone argues about a result.
02
Models may map and flag. People accept or discard. Nothing is certified by a model.
03
Reports state scope, methods, findings, and what the work does not decide.
What we test
These are laboratory disciplines in development — not market licenses.
IND-01
Architecture for evaluating modern software systems, model-assisted products, cloud services, and programmatic interfaces.
IND-02
One laboratory vertical — skill, amusement, mathematics, RNG where in scope, kiosks, mobile, and web. Not a casino brand and not a gambling operator.
IND-03
Technical review of payment flows, settlement records, and related integrity controls when those artifacts are in scope.
IND-04
Integrity, configuration, and evidence-oriented security review as a testing discipline — not a managed security provider claim.
Inside the AI laboratory
Twelve assisted capabilities. One rule: the laboratory remains the author of every finding.
AI-01
Assisted inventories of modules, interfaces, and dependency surfaces from submitted artifacts.
AI-02
Candidate outliers in code, logs, or numerical series — each requiring human acceptance.
AI-03
Scenario generation and model-assisted rehearsal of stated paths. Simulations are not field proof.
AI-04
Clustering and timeline assistance across operational logs supplied for the engagement.
AI-05
Assisted assembly of exhibits, hashes, and cross-references for the laboratory record.
AI-06
Comparison of declared configurations, manifests, and environment snapshots.
AI-07
Draft cases and oracles proposed from requirements text. Staff decide what enters the plan.
AI-08
Assisted comparison of current artifacts against a prior, identified baseline.
Evidence-driven flow
Scope, parties, and confidentiality terms are recorded. Work does not begin on an undefined object.
Source, binaries, documentation, and access credentials are received under a custody record.
Hashes, manifests, and identity of the test object are confirmed before analysis proceeds.
Methods, environments, and acceptance of limitations are written down. The plan governs the work.
Where useful, models map and flag candidates. Machine output is advisory to laboratory staff only.
Human-directed testing executes the plan against the identified object and records observations.
A reviewer who did not solely produce the draft examines methods, evidence, and wording.
Quality review checks completeness, impartiality flags, and report-control requirements.
The issued report states scope, methods, findings, and limitations. It is the controlled work product.
Material changes to a previously tested object require a new or supplemental engagement. A prior report is not continuous monitoring.
Built for trust
GA Skill Games, LLC owns the laboratory company. Owners may fund buildings, tools, and time. They do not edit findings. Ownership does not determine outcomes. Evidence does. Owners control strategy and resources, not laboratory findings.
Quality system
A quality system is being written so methods, records, impartiality, and corrections can be controlled. That is readiness work.
Research
ETTC research exists to improve laboratory methods. It does not sell a consumer product. Notes will appear here as they are cleared for public release.
RS-01
How laboratory staff should accept, amend, or discard model output so that AI never becomes the certifying actor.
RS-02
Hash, manifest, and custody practices that keep the tested object identical to the object named in the report.
RS-03
Technical methods for interactive systems where skill or deterministic rules — not spectacle — are the object of review.
RS-04
How to state uncertainty when data are finite, biased, or supplied only by the client.
Work with ETTC
Submit a project brief by form. Mail to Cheyenne headquarters. Public telephone is on Contact and in the footer.