Independent Grid Data & Analytics
The American grid is entering its largest capital cycle in a generation. RAG gives regulators, legislators, and public-interest stakeholders the same curated data and explainable, physics-informed analytics that utilities, developers, and financiers already use — so that spending is justified, not merely asserted.
For more than a decade, decarbonization goals supported elevated utility capital budgets despite relatively modest demand growth. Today, demand growth has returned — unevenly and unpredictably — driven by industrial electrification, reshoring, and clusters of large, flexible and inflexible loads.
Regulators and legislators are being asked to approve or absorb unprecedented capital spending without access to independent, explainable analytics on par with those used by utilities, developers, and financiers. — RAG Business Plan, Executive Précis
RAG's analytics combine tested Physics-Informed Machine Learning (PIML) with mechanically explainable, power-grid-specific deep learning — designed from the outset to be interpretable by non-specialist decision-makers, not just by the engineers who built them.
RAG is independent of the AI industry, data center developers, utilities, independent power producers, and energy producers. Our competitive advantage rests on serving the public interest in a fair distribution of costs and benefits — not the private interest of any single class of market participant.
Results are explainable, auditable, and suitable for regulatory and legislative proceedings. Models are built to test counterfactuals — not merely to optimize within existing institutional constraints — and data is curated, documented, and privacy-protected throughout.
Two modules are in active beta build-out; two more are next in the development queue, informed by subscriber and public-sector requirements — beginning with the Kentucky Public Service Commission's requirement for just and reasonable transmission cost allocation.
Screens reliability-justified rebuild filings against reconductoring, dynamic line rating, and grid-enhancing-technology alternatives.
Compares the cost and reliability of serving large loads via local generation, pipeline capacity, HVAC transmission, or a dedicated DC interconnector.
Maps ride-through and ROCOF exposure from inverter-based resources and proposes grid-enhancing-technology mitigations.
Compares battery and gas storage against transmission and pipeline build-out on reliability contribution per dollar and per month.
Subscribers access all modules through RAG's analytics console — live data, counterfactual modeling, and exportable staff memos.
Preview the Console →A tiered subscription model, with base charges and additional use-based analytics and data charges as required.
Basic data, analytics, and news access to inform local economic and political activity.
Request AccessExpanded data and analytics for power and data-center users, priced further on use intensity.
Request AccessFull module and data access, with secure enclaves for private exchange of proposed cases and plans.
Request AccessInstitutional-tier access for federal and state regulators, legislative committees, and national laboratories, at appropriate discount.
Request AccessIndependent, grid-development-specific reporting from RAG's editorial desk and contributing writers.