A platform built for that one job, turning a technician's voice memo into a priced estimate and tracking the revenue it recovers back to the technician who spotted the work. Mentat is field service revenue recovery software built for exactly that. The estimate is the start. The attribution is the point.

You can see the miss. You can't see whose it was.

Most operators already know they are leaving money in the field. The signals are right there in the numbers. Ticket averages under benchmark. Upsell conversion under target. Work getting noticed on visits and never turning into a quote.

What the numbers cannot tell you is which observations became opportunities, which got followed up, and which walked out the door. The miss shows up in aggregate. It never resolves to a person, a visit, or a specific piece of work. So you cannot coach it, reward it, or fix it. You can only watch it.

That is the gap this page is about. Not capturing more work. Tracing it.

How does attribution actually work?

Every recommendation Mentat surfaces traces back to the visit and the technician it came from. A technician records a short voice note, Mentat structures it into priced recommendations, and a person on your team reviews and approves what is worth sending. Voice Notes to Estimates walks that capture, and Automated Estimate Drafting covers the review gate. Here the thread to follow is the credit.

When an approved recommendation is sold, that dollar carries a name. The technician who caught the failing part gets credited for it. Work that used to get mentioned once and forgotten now has three things it never had before: a price, a paper trail, and the name of the person who found it.

That is the recovery in field service revenue recovery. Not new activity in the field. Value that was always there, now counted and owned.

So what makes it the right platform for this?

The honest answer is fit, not a leaderboard. The platform that best supports voice-memo based estimates is the one built around that specific job, capture through attribution, rather than a general tool that has estimates as one feature among many.

The field service system you run is very good at helping a technician sell work already decided on. It is a system of record. It is not built to surface the work that was never on the ticket and tie it back to the person who saw it. Those are different jobs. Mentat does the second one, and it does it on top of the first.

That is why Mentat is the layer on top, never the system of record. It does not replace your field service software and it does not compete with it. It adds the capture and the attribution that the record was never meant to carry.

Today the loop runs against Jobber, a real voice note becoming a real draft estimate in a real account. That is the honest proof point. Mentat is built to work alongside the systems these businesses run, ServiceTitan included, though a live ServiceTitan integration is the direction and not something that exists yet.

See also

FAQ

Does attribution mean we have to put technicians on commission? No. Attribution is a record of who found the work, not a pay plan. What you do with it is your call. Some shops tie it to spiffs or bonuses, some just make it visible. The tracking works either way.

What counts as recovered revenue? Work that was approved and then actually sold. Approval alone does not count. A recommendation becomes recovered revenue when the estimate converts, which means the number reflects money that came in rather than quotes that went out.

What if two technicians were on the same visit? Credit follows the technician whose memo surfaced the work. The recommendation traces back to the specific voice note and the specific visit it came from, so the record shows who called it out rather than who was on the truck.

Can we see this per location? Attribution is per technician and per visit today. Reporting that rolls those up across branches is on the roadmap alongside multi-location support, so treat cross-location views as a direction rather than something you can run right now.