What we do · 01
Where AI earns its keep in a home service company, and where it is a distraction. Fractional leadership so adoption does not depend on you pushing it through every week.
Where it pays
Inbound call capture and CSR support
After-hours and overflow calls that currently go to voicemail are booked jobs you already paid to generate. Drafted responses and call summaries let a good CSR handle more without dropping quality.
Call review at scale
You record calls and nobody has time to listen to them. Reviewing all of them surfaces missed opportunities, pricing hesitation, and which technicians need coaching on what.
Estimate and paperwork drafting
Job notes into a clean estimate, warranty letter, or permit packet. The technician still owns the number; the typing stops eating evenings.
Dispatch and scheduling triage
Ranking the board by margin, drive time, and membership status rather than by who called first. Suggestions to a dispatcher, not an autopilot.
Reporting and weekly briefs
Turning exports from your field service software into a short written brief a GM can read on Monday, instead of a dashboard nobody opens.
Follow-up that actually happens
Unsold estimates, expiring memberships, and review requests worked consistently, because the sequence does not depend on somebody remembering.
Where it does not
Replacing technicians
The labour constraint in this industry is licensed hands. Nothing here fixes that, and any vendor implying otherwise is selling you a story.
Anything that speaks to a homeowner unsupervised
Emergency calls, code compliance, and pricing carry liability. A person stays in the loop on all three, permanently.
AI on top of untrustworthy data
If your job costing is wrong, automation makes the wrong answer arrive faster and with more confidence. That is why data work comes first.
Tools nobody owns after launch
A pilot that lives on the founder’s laptop is a liability in diligence, not an asset. Anything we build gets an owner, a runbook, and a running cost you know.
What you get
Every engagement produces a short written recommendation before anything gets built: the workflow, the expected effect on a specific number, the monthly running cost, and who owns it once it is live. If the arithmetic does not work, we say so and you keep the money.
Plain-language tradeoffs
Written for an owner, not an engineer. What it does, what it costs, what breaks, what it cannot do.
Implementation, not a slide deck
We build and wire it into the software you already run, then sit with the people who have to use it.
A named owner inside your company
Someone on your team is trained and accountable, because an unowned tool dies the first busy week.
Documentation a buyer can read
Runbook, vendors, costs, and failure modes. This is the difference between an asset and a pilot.
In diligence
Buyers do not price your tool list. They price labour dependency, throughput per truck, and whether the process survives the person who built it. Framed that way, the AI conversation stops being about software and starts being about margin and transferability, which is the only version of it worth having.
Tell us the shop: trades, trucks, markets, and whether you are scaling, selling, or undecided. If we are not the right fit, you will hear it on the first call.
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