Plain Theory Labs
Plain Theory Labs is an independent certification framework for AI compute infrastructure. We measure what GPU clusters are actually doing, score it against a documented methodology, and deliver findings against a published standard.
What PTL produces
Section titled “What PTL produces”A PTL certification is a PTL Score — a number between 0.0 and 1.0 — derived from up to nine analytical engines running independently against your operational data. The score determines your certification tier. The tier is shorthand. The score is the truth.
Nine engines
Section titled “Nine engines”Each engine addresses a distinct dimension of infrastructure performance:
Data collection. PROFILE characterizes your cluster — scheduler type, GPU fleet, telemetry sources — and routes data to downstream engines. CLAW is the intake agent that automates data collection where permitted.
Efficiency measurement. ACE (Adaptive Compute Efficiency Engine) measures GPU utilization from Slurm, Kubernetes, or DCGM telemetry. PACE measures scheduler efficiency — how well your cluster allocates resources across competing workloads.
Facility and hardware. COOL measures cooling system performance relative to a PUE benchmark. FLUX grades your carbon accounting methodology. CORE evaluates hardware-workload fit, fleet age, and embodied carbon.
Certification and recommendations. GRADE aggregates engine scores into a composite PTL Score and produces the certification report. ATLAS generates a ranked action plan — the specific changes most likely to improve your score in the next assessment.
Longitudinal certification
Section titled “Longitudinal certification”A PTL certification is not a one-time audit. Year one is a baseline. Year three is a dataset. Organizations that improve from DEVELOPING to CAPABLE to OPTIMIZED across assessments have a record that regulators, funders, and procurement offices can evaluate. PTL maintains the certification record. You own the findings.
Get started
Section titled “Get started”Read how certification works or start a pilot.
Repositories
Section titled “Repositories”| Repository | Description | License |
|---|---|---|
| ptl-engines | All nine analytical engines — 864 tests | MIT |
| ptl-methodology | Scoring formulas, coefficients, tiers | CC BY 4.0 |
| ptl-website | This documentation site | MIT |
| ptl-context | Engineering context and session logs | Private |
All methodology is public and citable. Source code is open under MIT license. The organization is at github.com/plain-theory-labs.