Rumixr puts manual-aware AI, camera-based detection, and live expert collaboration inside every repair task — so technicians spend less time hunting for answers and more time fixing equipment.
Chat, detect, and call an expert without leaving the task.
Grounded in your docs
Expert, on the call
Findings captured as you go, not after
No flagship features described in a pitch and missing in the product. This is what's live, in the app, right now.
An assistant scoped to the task at hand — grounded in equipment manuals and documentation, with voice input for hands-busy technicians.
Point a camera at the equipment and get real-time component identification to speed up diagnosis — no guessing which part you're looking at.
Pull a remote expert into a live video call with annotation directly on the shared feed — like they're pointing over your shoulder.
Tasks, notes, and reports live in one connected workspace, so field knowledge doesn't get lost across five different tools.
A technician opens an assigned task with full context — equipment, history, and documentation already attached.
Chat with the AI assistant, point the camera for detection, or call in a remote expert — whichever the situation needs.
Notes and findings attach to the task as you go, instead of living in a notebook or a text thread that gets lost.
Wrap the task with a structured report, AI-assisted from what was already captured — ready for the record.
Founded by a biomedical engineer with 10+ years fixing the exact equipment your team services — not a generic AI wrapper.
A tight set of capabilities that work end to end, instead of a long feature list where half of it is aspirational.
Rumixr supports the technician's judgment — it doesn't replace it. Every decision stays with the person doing the work.
Designed for small-to-mid service companies and ISOs, where getting started doesn't take a six-month procurement cycle.
"Technical knowledge shouldn't leave the building when an engineer does. It should stay in the system, ready for the next person on the job."
Not projected numbers — just what a task looks like before Rumixr, and after.
Technician stops mid-repair to search through a PDF manual for the right procedure.
Asks the task-scoped AI assistant directly and keeps working, hands mostly free.
Guesses which component they're looking at, or digs through documentation to confirm.
Points the camera and gets the component identified on the spot.
Calls a remote expert and tries to describe the problem over the phone.
Pulls them into a live video call — the expert sees exactly what the technician sees, and can annotate it.
Findings end up scattered across texts, a personal notebook, or nowhere at all.
Notes attach to the task as they go, ready to become part of the closing report.
A 15-minute walkthrough, on a task that looks like the ones your technicians handle every day.