OnPoint by LeanFM

Turn BAS data into ranked HVAC action.

OnPoint analyzes existing BAS exports to surface hidden HVAC faults, estimate likely impact, and help teams decide what to fix first.

OnPoint is LeanFM’s building system intelligence product for turning trend data into clear operational priorities. It is powered by the Prescriptiv analytics engine, developed from research at Carnegie Mellon University.

Person using a BAS workstation or reviewing building system data

Prioritized diagnostic finding

AHU-3 heating and cooling conflict

High Priority

Cooling and reheat appear active during occupied periods, creating avoidable energy use and comfort instability.

Energy waste

Comfort risk

Equipment wear

Evidence reviewed

RuntimeSetpointsSchedulesSensors

Recommended action

Review sequence logic and occupied schedule behavior.

The problem

BAS alarms miss faults that still hit the bill.

Building teams already have trend data, but costly HVAC behavior often stays buried until someone has time to investigate manually. OnPoint turns those exports into a ranked list of what deserves attention first.

Stuck dampers
Simultaneous heating and cooling
Economizer failures
Sensor drift
The workflow

From raw BAS export to ranked action.

The point is not more charts. It is a defensible shortlist of faults, likely impact, and next actions your team can work through.

01

BAS export

Start with the data you already have

Use CSV trend exports from your current BAS/BMS. No new hardware or site install required.

02

Fault signals

Surface what alarms miss

OnPoint looks for behavioral patterns that point to hidden HVAC waste and comfort risk.

03

Ranked action

Fix what matters first

Findings are prioritized by likely energy, comfort, and operational impact.

Existing BAS Data

Runtime · Setpoints · Schedules · Sensors

Hidden Patterns

Waste · Drift · Conflicts · Logic Faults

Clear Actions

Prioritize · Assign · Resolve

Illustrative product output

From noisy data to a prioritized fix list.

OnPoint is designed to move teams from scattered BAS exports and alert noise toward a ranked list of actions.

Noisy BAS exports / alarm list

AHU trend export 04.csv
Alarm list: 183 active items
Schedule overrides
Sensor values by zone

Ranked action list

1AHU-3 simultaneous heating/cooling
2RTU-2 excessive runtime
3Zone sensor drift
4Schedule override review

Illustrative example, not a live software screenshot.

Why it matters

Every fault competes for attention. Rank by impact.

OnPoint helps teams connect hidden system behavior to operational outcomes: energy cost, occupant comfort, equipment reliability, and emissions.

Budget

Ranked waste

Hidden HVAC faults prioritized by likely cost, comfort, and operational impact.

Comfort + reliability

Priority list

A clearer shortlist for issues that affect occupants and equipment performance.

Emissions

Less waste

Operational fixes help reduce avoidable energy use in existing buildings.

Operational waste is measurable

DOE guidance highlights the importance of reducing commercial building energy waste through practical operational improvements. View source

Building performance is climate work.

Architecture 2030 reports the built environment is responsible for over 35% of annual global CO2 emissions. View source

Who it is for

Built for teams accountable for real buildings.

Owners need cost visibility. Facilities teams need a practical first move. Energy leaders need credible efficiency opportunities.

Building owners

See which hidden HVAC issues may be affecting operating costs and asset performance.

Facilities teams

Get a practical fix list instead of another dashboard full of noise.

Energy leaders

Identify operational waste that can be addressed without starting with capital projects.

Turn your BAS data into a ranked fix list.

Use the exports you already have. OnPoint will show where hidden HVAC faults are most likely costing you.

Prioritized diagnostic finding

Hidden runtime pattern surfaced

High Priority

Existing BAS trends can point to issues worth reviewing before they become larger operating problems.

Energy waste

Comfort risk

Equipment wear

Evidence reviewed

RuntimeSetpointsSchedulesSensors

Recommended action

Review sequence logic and occupied schedule behavior.