Your most expensive resource — engineering time — is consumed by early-stage assessments on projects that never move forward. Energy Pilot AI handles the screening so your team can focus on billable work.
When a potential client calls about a retrofit project, your engineers spend 40–80 hours on preliminary assessment before you know if the project will be funded. That's time they're not spending on plan/spec work that generates revenue.
The worst part: most early-stage screening doesn't require detailed engineering. It requires a credible baseline and directional savings estimates — which is exactly what ML can deliver in minutes instead of weeks.
You've experienced the pain of building a baseline from 5 months of bills. Traditional change-point regression falls apart below 8 months. Our ML models don't.
5-parameter models require 12+ months of continuous data for reliable baselines. Below 8 months, prediction error degrades exponentially. At 3 months, results are essentially unusable.
Models trained on 10M+ calibrated EnergyPlus simulations. Transfer learning compensates for sparse billing data. Calibrated uncertainty bands narrow as more data arrives.
Two modules designed for the engineering firm workflow — fast preliminary assessment and systematic on-site data collection.
Start with an address. Add utility bills as they come in. Studio produces hourly energy baselines and ECM savings forecasts with confidence intervals — the defensible preliminary assessment your clients need.
Replace ad-hoc field notes with standardized digital audits. Equipment inventories, photos, and observations flow into structured data that feeds directly back into Studio's forecasting models.
Energy Pilot AI is built by a team with deep building energy science expertise. Our models are validated against ASHRAE standards — not just marketing benchmarks.
Pick a building in your pipeline with incomplete utility data. We'll show you what Studio produces — and let your engineers judge the baseline quality themselves.
Schedule a Demo →