Buildings rarely fail loudly. A leaking valve, a stuck damper, a drifting sensor or an economizer running backwards will not raise an alarm — the space stays roughly comfortable while the plant works far harder than it should. The cost shows up on the utility bill and in equipment life, months later, attributed to nothing in particular.
Status: product concept, in active development. This is something we are building, not something you can buy today. We publish our roadmap because the engineering thinking behind it is the useful part — and because we would rather show you the design than imply a finished product.
Designed Capabilities
- Equipment templates and tagging — apply diagnostics across a fleet without hand-configuring each unit.
- Streaming rule and model execution — faults detected continuously, not in a quarterly review.
- AHU, VAV, RTU, chiller and boiler fault libraries — the failure modes that actually recur.
- Confidence and persistence scoring — a fault seen once is noise; seen for a week it is real.
- Trend evidence visualization — the data behind the finding, not just the finding.
- Likely-cause and diagnostic guidance — what to check first when you get there.
- Operational and energy impact estimation — what this fault is costing.
- Workflow integration and resolution tracking — findings become work orders and get closed.
Evidence, Not Alerts
FDD tools fail when they produce more alerts than anyone can action — teams learn to ignore them, exactly as they do with over-sensitive alarms. Confidence scoring, persistence and cost impact exist so the output is a short ranked list a technician can trust, with the trend data attached to justify the trip.
Tell us if this matches a problem you have — early input shapes what we build first, and we will give you an honest view of where it stands.