Candor Intelligence
A framework for real-time carbon verification of enterprise cloud workloads — with AI scope broken out for defensible Scope 2 reporting. Grid-matched, not REC-based.
The world's largest technology companies are spending billions on Renewable Energy Certificates while their actual cloud emissions climb year over year — and AI workloads are accelerating the curve. The problem isn't a lack of renewable energy investment; it's a complete absence of real-time, independent verification tying that investment to actual workload consumption.
A company can purchase RECs from a wind farm in Wyoming to cover a data center in Virginia running on coal. No temporal matching. No geographic matching. No connection to reality.
— The REC credibility gap, explained
Regulators are catching up. The GHG Protocol is updating Scope 2 guidance in 2026. The SEC, EU, and California are tightening reporting requirements. The 24/7 Carbon Free Energy standard — which requires hourly grid matching — is becoming the benchmark serious enterprises are measured against.
This initiative establishes a framework for enterprises operating cloud workloads — with explicit AI-scope segmentation — to verify, not estimate, the carbon intensity of their compute at the moment of execution. The approach is grounded in four principles:
Rather than relying on annual REC reconciliation, this framework connects enterprise cloud infrastructure directly to live grid carbon intensity signals — producing a verifiable, timestamped record of how clean the grid was when each workload ran, with AI-scope broken out for Scope 2 disclosures.
The initiative targets enterprises that have made public net-zero commitments and carry Scope 2 reporting obligations on their cloud footprint — particularly those with meaningful AI workload exposure and facing increasing scrutiny from ESG investors, SEC disclosure requirements, and climate-focused procurement standards.
The core claim is deliberately conservative and defensible: grid cleanliness at the time of workload execution — aligned with the GHG Protocol Scope 2 location-based methodology and the emerging 24/7 CFE standard.
Every cloud workload is matched against live Marginal Operating Emissions Rate (MOER) data from WattTime — the most defensible signal for Scope 2 reporting. No averages. No annual reconciliation.
GPU instances are segmented from general compute inside the total cloud footprint. LLM API usage is tracked separately with explicit "estimated vs. verified" labeling. Enterprises get a defensible AI-scope breakdown — not a blended cloud average.
Verification is performed by an independent third party — not the cloud provider. Every workload is logged to an immutable database with timestamp, region, instance type, energy estimate, and grid signal. Any auditor can trace the chain.
14-day historical grid patterns enable enterprises to shift workloads toward lower-carbon windows. Verification becomes a continuous improvement loop — not just a compliance checkbox.
Enterprise connects AWS, Azure, or GCP accounts via read-only credentials. No write access, no operational risk. CloudWatch and billing APIs pull instance-level data.
GPU instances are identified by type (p4, p3, g5 on AWS; NC/ND on Azure; TPUs on GCP) and segmented from general compute. The AI scope is tracked and reported in parallel with the full cloud footprint, never replacing it.
Each workload's execution window is matched against WattTime's MOER signal for the corresponding grid region. TDP-based energy estimates — industry standard methodology — are clearly labeled as estimates.
Every workload is written to a timestamped, append-only database record: org, timestamp, cloud provider, region, instance type, hours, kWh, carbon intensity, CO₂ (kg), and renewable percentage.
An audit-ready Scope 2 compliance report is generated — exportable for SEC filings, CDP submissions, SBTi reporting, or investor ESG due diligence. AI scope and total cloud scope are reported separately.
This initiative is designed to align with the regulatory frameworks that will govern enterprise cloud emissions reporting — with AI-scope disclosure — through 2028 and beyond. The methodology is conservative by design, defensible against the most rigorous interpretations of each standard.
The GHG Protocol is updating its Scope 2 guidance in 2026 — rules that will determine what counts as a credible renewable energy claim are being written right now. Enterprises that establish real-time verification practices today will be positioned ahead of compliance requirements, not scrambling to meet them.
WattTime MOER integration active on CAISO_NORTH. First verified reports generated. AWS CloudWatch connection in progress. Backend deployed to Railway.
Full AWS integration with job-level workload tracking. Legal entity formed. First 3–5 pilot customers at discounted rate. WattTime Analyst tier negotiated.
Azure and GCP integrations. Real-time dashboard for enterprise customers. Automated scheduling recommendations. Seed raise initiated.
Established as the independent verification layer for enterprise cloud carbon claims — including AI-scope segmentation — the Bloomberg of cloud carbon data. SOC 2 certified. Series A.
Enterprises with public net-zero commitments and meaningful cloud workload exposure — with AI accelerating the curve — face a widening credibility gap between their REC-based claims and actual emissions. We're building the verification infrastructure to close it.
We're currently in conversations with early enterprise partners, sustainability teams, and climate-focused investors who want to get ahead of the regulatory curve.