AI infrastructure measurement, metrologically grounded.
Machina turns GPU degradation from an unpriceable risk into a covenant-grade asset class.
AI infrastructure debt is a $20T+ market that institutional capital cannot price.
No measurement basis
GPU degradation has no metrologically traceable measurement standard. Lenders, insurers, and rating agencies have no common ground for pricing the asset.
No covenant-grade attestation
Trustee platforms cannot ingest GPU health data because no independent attestation source exists. Covenant feeds in other infrastructure asset classes use measurement; in AI infrastructure they do not exist.
No insurance product
Without measurement, residual value risk cannot be insured. The compute tranche of every AI infrastructure deal is funded as private credit or equity, never as IG-rateable debt.
The Machina platform
Measurement first. Then attestation. Then markets.
Metrological foundation
GPU degradation reduced to a traceable number
Machina's measurement engine runs standardised workload kernels against each GPU and records cycle-accurate performance metrics. Every result is timestamped, signed, and anchored to an SI-traceable reference — giving lenders and rating agencies a defensible basis for the first time.
Covenant-grade attestation
Independent attestation that trustee platforms can ingest
Each measurement run produces a signed Covenant Feed — a structured JSON document that maps directly onto standard infrastructure covenant templates. Trustees can ingest it programmatically, removing the last manual step between hardware health and financial reporting.
Portfolio intelligence
Fleet-level risk analytics for AI infrastructure deals
Aggregate RUL distributions, survival curves, and scenario-stressed residual values across an entire portfolio. Machina surfaces the numbers that actuaries, credit committees, and rating desks need to move AI compute from private credit into IG-rateable debt.
Credibility
Built on standards, validated in live transactions.
NPL Partnership
Measurement protocol co-developed with the National Physical Laboratory — the UK's primary national measurement institute.
GB2630720
Patent granted for the metrologically traceable GPU degradation measurement method underpinning every Machina attestation.
Case study: Barranquilla
Covenant feed delivered for a 4 MW GPU cluster financing, enabling a structured credit tranche that would otherwise have been equity.
Case study: CoreWeave DDTL
RUL analytics integrated into a delayed-draw term loan structure for a hyperscale AI infrastructure operator.
Ready to put a number on your GPU fleet?
Request a demo to see a live Covenant Feed generated from your infrastructure, or read the white paper for the full measurement methodology.