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Evidence for compute governance

AI infrastructure records for research on ownership, supply dependencies and compute policy.

Why Scrutica exists

A facility’s power capacity alone says little about the training it can support. The answer depends on its hardware and utilization; regulatory reach also depends on the companies behind it and the jurisdictions they operate in.

What Scrutica covers

4,576
facilities
110
countries
18,980
supply-chain records
36
sovereign programs
55
public query tools

Sources include Epoch AI’s facility and GPU-cluster datasets, the Federal Register, SEC EDGAR, CSET ETO and licensed corporate databases. The methodology page describes their coverage and the gaps that affect the analysis.

What's in the platform

Records cover the physical infrastructure and the organizations responsible for it.

The Query Builder answers questions over these layers in natural language, using 55 tools for records, calculations and page content. The MCP server exposes 10 read-only tools for use in an agent client.

Which number to cite

The platform totals below use the snapshot dated 2026-09-11. Individual pages and Query Builder results may use a different date or population. Cite the result you used, with its date and scope.

QuantityValueCoverageVintageDefinitionCurrent comparison
Facilities4,576all recorded facilities, across classes and statuses; includes records from licensed sources that are not publicly readable2026-09-11the substrate snapshotPublicly readable facilities: 4,260 at last render. Public access excludes the licensed-source records included in the total.
Countries110distinct country codes in facility records2026-09-11the substrate snapshotCounted when the snapshot was created; no current comparison is run here.
Supply-chain records18,980all supply-chain records, including licensed sources and repeated reports of the same relationship2026-09-11the graph scopeThe underlying records have restricted access. This total is counted when the snapshot is created.
Distinct supplier–customer relationships14,937distinct combinations of supplier, customer and product or service, after company identities are reconciled2026-09-11the graph scopeCounted when the snapshot was created, after duplicate relationships were removed.
Export-control designations3,435recorded export-control designations, with Federal Register sources2026-09-11the substrate snapshotCurrent count agrees (3,435)
Designation-to-company matches176active matches between designations and company records; a designation can have several matches2026-09-11the substrate snapshotMatch records have restricted access. This total is counted when the snapshot is created.
Sovereign programs36national or regional government compute programs in the curated list2026-09-11the programme listCounted from the current curated program list.
Public query tools55tools available to the public Query Builder; excludes administrative toolscurrent tool listthe tool listCounted from the Query Builder’s public tool list.

Limitations

  1. Coverage depends on disclosure. Public-company filings can identify subsidiaries and ownership relationships that remain unknown for private or state-owned operators; missing reports also limit facility-capacity estimates.

  2. Power and capital cost support capacity estimates only through assumptions about the hardware they serve. Hardware inventories reduce that uncertainty, but utilization and training duration still affect estimates of how much compute a facility can supply.

  3. A reported supply relationship rarely establishes how much production would be lost if it failed. The cascade model uses default supply shares where values are missing and analyst-selected propagation rates; estimated severity depends on those assumptions.

Built by

David Gringras
Frank Knox Fellow, Harvard · MPH Health Policy

David Gringras, physician (Edinburgh) and law graduate (University of Law), Frank Knox Fellow at Harvard (MPH Health Policy, 2026; cross-registered at MIT, Harvard Law School, and the Kennedy School). Expert panelist and co-author on the Evals-Consensus.AI Delphi study of AI evaluation practice; supported by a BlueDot Impact career transition grant. Previously Evaluations and Collaborations Lead on the FATF-to-AI governance translation project at Arcadia Impact / The Future Society, and project supervisor at Orion AI Governance on evaluation-independent governance mechanisms.

davidgringras@hsph.harvard.edu

Corrections

Send corrections or methodological criticism to the address above. Published corrections are listed at Corrections.