LeanFM reads the building automation data you already collect — analyzed by Prescriptiv, our engine developed from Carnegie Mellon research — to uncover energy waste, comfort issues, and maintenance risks. No new sensors required.
$105,000/yr identified · 220,000 sq ft school · existing BAS data only
Backed by our 3–5× money-back guarantee.
Born at Carnegie Mellon. Proven in the field.
Your BAS alarms on thresholds — a fan fails, a sensor flatlines, you hear about it. But simultaneous heating and cooling, a stuck economizer, a schedule that never matched occupancy? Those run silently, sometimes for years, quietly burning five to six figures a year in a single building.
0 active alarms
Waste accruing daily
Same building. Same day.
Figures from independent building retro-commissioning research. Individual results vary by building; LeanFM's findings are reported per building from your own data.
Read-only access to the trend data you already produce — analyzed by Prescriptiv, our fault-detection engine developed from Carnegie Mellon research, then reviewed by engineers who do commissioning.
Two systems fighting in the same air — comfort holds, cost doubles.
Dampers stuck or mis-sequenced, paying for cooling the weather would do free.
Equipment running nights and weekends for empty rooms.
Sensors reading wrong, so controls act wrong everywhere downstream.
Overrides that never got reset, compounding year over year.
Cycling, short-starts, and hours far beyond what load requires.
Loops that hunt, resets that never engage, sequences drifted from design.
Flow stations reporting fiction while the BAS reports normal.
No sensors to install. No sequences touched. Just the trend logs your building has been writing all along — finally read closely.
AIR (Asset Intelligence Rating) rates building performance from 0–100 across energy, comfort, maintenance risk, and controls health — computed from your BAS trend data and updated with every analysis run. Open any rating and see the findings behind it: which equipment, which fault, which dollars.
Get your building's AIR scoreIllustrative score · every rating opens to its evidence
Ask why the third floor runs hot, why a unit's runtime jumped, or what to fix first before budget season. Maple answers like a senior engineer — with the trend data, the root cause, and the recommended action. Not a chatbot. A colleague grounded in your building's data.
See Maple on your data▸ Why did our gas usage jump in March?
Recommended: restore the prior reset schedule — about 30 minutes for your controls contractor.
$4,120 so farIn annual savings opportunities identified in one school — led by simultaneous heating and cooling and schedule faults that never tripped an alarm.
Get a complimentary analysisReported first-year savings — growing to $101,383 in year two — in one of the most demanding climate environments there is: art conservation.
Get a complimentary analysisWhere the Prescriptiv engine was developed — the Carnegie Mellon research behind every analysis we run.
Get a complimentary analysisEvery analysis: your AIR score, the top findings ranked by dollar impact, what was fixed, and what it returned. One dataset, three altitudes — board, finance, operations.
Download a sample reportLeanFM · quarterly summary
Building performance — AIR
74
AIR score · up 3 this quarter
Findings · ranked by impact
Top open findings
Savings · identified vs captured
What was fixed, what it returned
$0 – $0 / yr
Based on $/sq ft identified across LeanFM deployments in buildings like yours.
An estimate from deployment averages.
Get the verified number →Prescriptiv, our fault-detection engine, grew out of Carnegie Mellon research.
Every finding shows its evidence — the trend, the root cause, the dollars. No black box.
We analyze a data export. Nothing connects to your controls; nothing changes in your building.
Findings are reviewed by people who do commissioning before they reach you.
Send us trend data from one building and we'll return a sample analysis — real findings with real dollar values, no commitment. We'll confirm timing on a 20-minute scoping call.