Grid Analytics Co · Utility Grid Intelligence & Automation
Forecasting, grid analytics, engineering automation, and custom software built specifically for electric utilities.
From AMI, GIS, and SCADA to CYME, ADMS, DERMS, and production engineering applications, we turn fragmented systems into repeatable engineering workflows.
AMI / GIS / SCADA / PI / OMS / CYME / ADMS / DERMS
Illustrative data. Live builds connect to your systems.
The Utility Technology Gap
Utilities are surrounded by systems that were never designed to work together, and by engineering workflows that were never designed to scale. That gap is where grid modernization programs stall.
AMI, GIS, SCADA, PI, OMS, CYME, and customer systems each hold a piece of the truth, and they rarely agree with one another. The topology in GIS isn’t the topology in the power-flow model.
Load allocation, capacity math, and planning judgment sit in personal workbooks and tribal knowledge. When the engineer leaves, the methodology leaves with them.
Studies get done once, presented once, and shelved. Nothing becomes a repeatable workflow, a monitored process, or a production application that keeps answering the question.
Why Now
Four tailwinds are reshaping utility engineering at the same time. Each one lands on the same weak point: the grid model and the data underneath it. That is where we work.
Data centers, electrification, and onshoring ended two flat decades. Peak-demand forecasts have been revised upward every year since 2022, and large-load interconnection requests now arrive faster than planning teams can study them.
FERC Order 2222, IEEE 1547-2018, and state DER programs require utilities to model resources they cannot yet see. DERMS and managed charging only work on top of accurate connectivity and forecasting.
Second-generation meter deployments are underway across the country, and regulators increasingly ask utilities to show analytics value from the first generation. Most of that value is still sitting unused in interval data.
GRIP and IIJA federal funding, wildfire mitigation plans, and rate cases built around grid modernization all put budget behind the unglamorous work that makes programs succeed: data quality, grid models, and repeatable engineering workflows.
Solutions
Different entry points, one repeatable capability: organize the underlying data, encode the engineering logic, automate the workflow, and build a production solution around it.
Flagship
Build the forecasting capability your planning organization actually needs, not a tool bolted onto unready data. Short- and long-term load forecasting, spatial and 8760 forecasts, load queues, DER/EV growth, large-load requests, and scenario planning that actually reaches the power-flow model.
Deep dive: Load Forecasting →
Analytics
Unlock the engineering value already sitting inside AMI: theft detection, EV charging identification, load signatures, connectivity validation, transformer loading, anomaly detection, and data-quality analytics.
Deep dive: Power Theft Detection →EV Analytics →
Readiness
Don’t implement advanced grid technology on top of an unreliable grid model. We assess GIS, connectivity, device models, telemetry, and CYME/GIS/SCADA alignment before your ADMS, DERMS, or forecasting program depends on them.
Deep dive: DERMS & Flexible Interconnection →
Operations
Turn operational data into actionable engineering intelligence: hot-bank analytics, short-term forecasting, PI Historian analytics, regulator and switching anomaly detection, and dashboards that replace manual multi-system queries.
Deep dive: FLISR →Clearance Evaluation →
Grid Edge
Understand where electrification is happening before it becomes a capacity problem. AMI-based EV detection, adoption forecasting, transformer and feeder impact analysis, and managed-charging optimization.
Deep dive: EV Analytics →DERMS & FlexConnect →
Resilience
Convert wildfire and protection data into defensible operational decisions: PSPS impact analytics, mitigation prioritization, enhanced protection settings analysis, protection automation, and outage simulation.
Deep dive: Wildfire Mitigation →
Start Here
A fixed-scope engagement that answers one question before you commit to a major technology program: is the underlying grid data and operating model actually ready? Every assessment produces findings your executives can read and a remediation path your engineers can execute.
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Assessment → remediation → integration → implementation → monitoring
The Capability Underneath
Every solution area runs on the same architecture: utility data, organized; engineering logic, encoded; workflows, automated; and a production application on top. Custom doesn’t mean bespoke. Reusable components mean each utility gets a tailored implementation without paying to reinvent the foundation.
Warehouse / lakehouse, pipelines, validated topology, governed history
Load allocation, capacity math, standards, and planning methodology: encoded, versioned, testable
8760 forecasts, scenarios, AMI analytics, model-quality scoring, protection studies
Repeatable computation exposed to tools, models, and other systems
Dashboards and production apps engineers actually use, not one-time deliverables
Decision / Action
REUSABLE COMPONENTS
Interactive
A forecasting capability is only useful if engineers can interrogate it. Walk the hierarchy from system peak to a single customer: the load shape, the growth story, and the engineering question change at every level.
Smooth diversified system shape, the easy one to forecast.
ILLUSTRATIVE DATA · PRODUCTION BUILDS RUN ON YOUR AMI / SCADA / GIS HIERARCHY
Selected Work
Anonymized examples from work across utility planning, operations, and grid technology. The pattern repeats: a difficult engineering workflow, organized data, encoded logic, and a solution that keeps working after the engagement ends.
Ranked anomaly scoring across the service territory turned meter data into an investigation queue for revenue protection.
Level-2+ charging signatures detected from AMI interval data. Electrification located before it hits transformer capacity.
Historical loading + weather models flag banks approaching operational limits ahead of peak season, not during it.
Spatial and 8760 forecasting integrated with the load queue and DER growth, with results that flow into the power-flow model.
GIS / CYME / SCADA discrepancy analytics scored model integrity feeder by feeder, before ADMS depended on it.
Multi-day manual study workflows encoded and automated: the same engineering logic, now repeatable and reviewable.
Case studies are anonymized and describe problem patterns and outcomes. No employer algorithms, data, or confidential details.
About
Experience developed across a municipal utility, a major investor-owned utility, and a grid-technology startup: planning, operations, and product. That combination is the point: utility engineering, data engineering, analytics, and software development in one practice.
Start a ConversationEngineering automation, operational analytics, smart-meter analytics, data-quality solutions, and distribution-system applications built inside utility operations, where reliability isn’t optional.
Long-term forecasting, scenario planning, CYME and LoadSEER workflows, capacity analysis, DER forecasting, and development of next-generation planning processes.
EV/DER optimization and utility software products built in a grid-technology startup environment: APIs, analytics, and production software shipped to real users.
Engagements
A fixed-scope readiness assessment or opportunity review. You get findings, scores, and a remediation path, whether or not we build anything.
Design the data foundation, engineering logic, and application around your systems, standards, and methodology, not a vendor’s.
Implement in increments engineers can validate: pipelines, calculations, analytics, and the production application on top.
Monitoring, model updates, and support: the capability keeps answering the question as the grid changes.
Start small. Prove value before the big program.
Contact
Tell us what you're planning (a forecasting program, an ADMS rollout, an AMI analytics initiative) and we'll tell you honestly whether a readiness assessment, a build, or neither is the right next step.