AI Implementation Advisory
Most AI initiatives fail on measurement, governance, and adoption — not on models. We bring the econometric discipline to prove what works, and the engineering depth to make it stick, with dedicated practices for the public sector and utilities.
A Proven Approach to AI Implementation
From initial assessment to full deployment, our structured methodology ensures every engagement delivers measurable, lasting impact.
Assess & Roadmap
We audit your data assets, infrastructure, and workflows; identify high-value use cases; and build an ROI-ranked roadmap. Because we are economists first, business cases are modeled with the same rigor we'd bring to an impact evaluation — including counterfactuals, not just projections.
Build & Pilot
Controlled pilots with causal measurement designed in from the start — randomized rollouts where possible, quasi-experimental designs where not. You'll know precisely what the AI changed, for whom, and at what cost.
Deploy & Scale
Production deployment with monitoring, drift detection, governance documentation, and staff training. We stay engaged through continuous evaluation so performance holds up long after launch.
AI for governments that answer to the public
Public agencies face constraints private firms don't: procurement rules, records laws, equity mandates, and hard scrutiny of every automated decision. Our public-sector practice is built around those realities.
Municipal Operations
Permit triage, records processing, 311 intake, and internal knowledge assistants that cut cycle times without cutting accountability.
Resident-Facing Services
Multilingual discursive agents for benefits navigation and service requests — bias-audited and equity-tested before they ever face a resident.
Program Evaluation & Compliance
Causal evaluation of AI-assisted programs, grant reporting support, and documentation aligned with NIST CSF 2.0 and FIPPs accountability principles.
Transparent, Defensible AI
Explainable models, immutable audit trails, and plain-language reporting your council, board, or auditor can actually read.
AI built on deep power-sector experience
We've spent years inside billing systems, AMI streams, and power-sector infrastructure data. That fluency means our AI work starts at the use case — not at a six-month data-discovery detour.
Load Forecasting & Nowcasting
Short- and long-horizon demand models combining machine learning with structural econometrics for forecasts you can defend to regulators.
Demand Response & Program Optimization
Propensity modeling, behavioral nudges, and digital-twin simulation to target the right customers with the right program at the right time.
AMI & Sensor Analytics
Anomaly detection, disaggregation, and predictive maintenance on high-frequency meter and sensor data at utility scale.
Regulatory-Grade Privacy
Customer energy-usage data handled under CPUC privacy rules, with differential privacy and synthetic data where analysis must be shared.
Start with an AI readiness assessment
A focused engagement that maps your data, ranks your use cases, and hands you a defensible roadmap — typically in weeks, not quarters.