Equipment from photos
See how Noma AI reads equipment photos and matches evidence to each unit.
During property fieldwork, Noma AI checks uploaded inspection photos for supported equipment. Review the resulting equipment details in the mobile visit and the report draft.
Read visible details
AI can identify water heaters, furnaces and boilers, air conditioners, heat pumps, and electrical panels. It reads visible facts such as brand, model, serial number, and a printed manufacture date. Supported type-specific details can also be filled from the photo.
Unreadable details stay blank. A photo without a readable label can still identify a supported unit. The photo reading does not diagnose the unit's condition or invent hidden details.
Match the same unit
Noma compares new photos with equipment already saved in this inspection. A label close-up and a wider view can become evidence for the same unit.
Distinct units stay separate, even when their brand and model match. AI can merge proven duplicate records when the photos establish that they show the same physical unit.
Photo crops: Famartin, CC BY-SA 4.0.
Review or correct the result
Open the unit, check its details against the evidence photos, and correct any field that needs it. Check model and serial numbers carefully. AI keeps your manual values, including a field you clear. After editing one field, recheck the others before finishing fieldwork.
Photo analysis needs a connection after upload. Saved equipment remains available in the app's local job data. A pending analysis is separate from saving your fieldwork.
Printed manufacture dates and supported serial-number rules can supply date details. Serial decoding and the default equipment paragraph use fixed rules, rather than another AI writing step.