Feature · AI carbon and energy governance
SentinelAI estimates per-model CO2e and energy use from training compute using provider grid factors and PUE, lets teams set monthly carbon budgets per tenant, and rolls results up to a portfolio-level sustainability view with budget utilization.
What this area covers
Carbon governance gives ESG, risk, and AI teams a way to account for the environmental footprint of AI work alongside its other governance dimensions. It estimates emissions and energy from training compute and tracks them against budgets so sustainability becomes a measurable part of oversight.
Related product areas
Maintain a governed inventory for AI models and use-case context with lifecycle state, ownership, risk posture, and supporting evidence.
Detect risks, duplicate AI initiatives, overlap, and rationalization opportunities across governed records with explainable, human-reviewed analysis.
Prepare executive reporting, audit-ready evidence views, and governance certificate workflows without overstating outcomes.
Generate a content-hashed AI Bill of Materials capturing model, dataset, and framework provenance, flag license conflicts, and export CycloneDX, SPDX, and PDF.
Operationalize evidence collection, control tracking, remediation, and framework mapping across AI systems.
Core capabilities
Estimate per-model CO2e and energy use from training compute using provider grid factors and PUE so the environmental footprint is quantified.
Set monthly carbon budgets per tenant so teams can hold AI work to defined sustainability targets.
Roll estimates up to a portfolio-level sustainability view with budget utilization so leadership can track emissions across the program.
Track how estimated emissions consume each tenant's budget so overruns are visible before they accumulate.
Keep carbon and energy estimates in the governance record so sustainability metrics support ESG reporting alongside other oversight data.
Target users
Governance value
How teams use it
Step 1
Estimate per-model CO2e and energy from training compute using provider grid factors and PUE.
Step 2
Define monthly carbon budgets per tenant to anchor sustainability targets.
Step 3
Roll estimates up to a portfolio sustainability view and track budget utilization over time.
Continue exploring
Maintain a governed inventory for AI models and use-case context with lifecycle state, ownership, risk posture, and supporting evidence.
Detect risks, duplicate AI initiatives, overlap, and rationalization opportunities across governed records with explainable, human-reviewed analysis.
Prepare executive reporting, audit-ready evidence views, and governance certificate workflows without overstating outcomes.
Generate a content-hashed AI Bill of Materials capturing model, dataset, and framework provenance, flag license conflicts, and export CycloneDX, SPDX, and PDF.
Operationalize evidence collection, control tracking, remediation, and framework mapping across AI systems.