Three portals — writer, tech, and manager — around one live board. Repair orders pull straight from your DMS, techs document with photos and video, and AI keeps customers informed without anyone picking up a phone out of guilt.
The writer pulls a repair order by number and the customer, machine, and every complaint line arrive from your DMS — scoped to the right store even when RO numbers repeat across locations. Assign a tech, set priority, mark ready-to-work.
Live columns from intake to complete, updating in real time as techs work. Ready-to-work flags, parts ETAs, priority customers, and attention alerts that use business days — not weekends — so Monday doesn't start with false alarms.
A tech's queue, big status buttons, and a job thread where photos, video, and cause-and-correction notes live forever with the job — searchable next time that machine comes back.
The moment a tech marks a job complete, AI reads the repairs that were actually performed — the cause-and-corrections, the parts, the complaints — and generates a QC checklist specific to this machine and this work. No generic form, nothing important skipped, no comebacks the customer finds first.
When a job's status changes, AI drafts the customer update in plain language. A writer approves it and it goes out as a text message. Every touch is logged, and the manager dashboard tracks contact cadence so quiet tickets can't hide.
Found extra work mid-repair? The writer texts the estimate. The customer taps a link — no app, no login — and approves or declines each service issue on its own, then signs. The shop sees the decision instantly and only does the work that was okayed.
Tech workload split, hours trends, intake vs. completion, QC flow, and a daily digest in your inbox before the morning huddle — across every location you run.