Every system is built from your ServiceTitan, HCP, FieldEdge, or Jobber data — and from watching how your best tech diagnoses, how your best CSR books, and how your dispatch lead assigns jobs. Not a generic model. Built for your operation specifically.
Most operators focus on tech performance. But the call that never gets answered, the estimate that never gets followed up, the membership that never gets offered — those leaks compound faster than margin drift in the field.
Your best tech closes at 38% GM. Your average runs 29%. No system measures the gap, flags the drift, or closes it. Across 50 techs, that's $400K–$800K/year in field service revenue leakage.
$8K–$16K per tech per yearInconsistent job execution drives callbacks. At $350–$600 fully loaded per event, a 50-tech shop burns $15K–$25K/month on rework nobody maps by root cause — but the data to reduce callbacks is already in your FSM.
$180K–$300K per yearYour best performers' knowledge lives in their heads. New techs take 6–12 months to ramp. Every branch runs differently because there's no system — just people.
$20K–$40K per new tech in slow ramp12–22% of inbound calls go unanswered during peak hours. Each missed call is a $300–$800 job that goes to your competitor. During peak season, that's $40K–$100K/month in lost revenue you never see.
$300–$800 per missed call in lost revenueYour best CSR books 85% of calls. Your average books 60%. Same phone, same leads, same zip code — 25 points of variance. Those missed calls and booking gaps add up to $150K–$350K/year in unrecovered revenue.
15–25 pts of booking rate spread35–50% of unsold estimates never get a follow-up call. Membership renewals slip. Post-service communication is inconsistent. These aren't tech problems — they're revenue left on the table by broken handoffs.
$150K–$350K/year in dropped follow-upsEvery operator has tried remote tools, training programs, and consultants who fly in for a week. They often fail for the same reason: they build from exported data and assumptions, not from observed reality. Our engineers embed in your operation and build from the inside out.
Vendor gets a Zoom walkthrough of your FSM setup, builds from screenshots and exports.
Off-the-shelf training content that doesn't reflect how your best tech actually runs a job.
Reports that show what happened but can't explain why — because nobody watched it happen.
Recommendations in a binder. No measurement loop. No one to adjust when reality doesn't match the plan.
Another login, another app, another thing dispatch has to remember. Adoption dies in week 3.
Our engineer sits with your dispatcher, watches job assignment logic, sees which techs get which calls and why.
We ride along with your best tech and your best CSR. The system is built from their actual decision-making, not generic best practices.
We see the tech who prices low because he's rushing. The CSR who loses bookings because she doesn't ask for the appointment. The patterns behind the numbers.
Same person who did the audit builds the system, deploys it, measures it, and adjusts it. No handoff. No translation layer.
Everything runs on top of your FSM and your existing call system. Your techs and CSRs keep doing their jobs. The system works around them.
This is what your team experiences on day one — not a kickoff deck.
Full day in the field. Watching job execution, pricing decisions, customer interactions, close technique.
Listening to live calls. Scoring booking attempts. Mapping how your best CSR converts vs. average. Noting follow-up gaps.
Sitting with dispatch. Watching job assignment. Pulling 6–12 months of FSM data. Beginning pattern analysis.
Same job types, different tech. Documenting where the execution path, pricing, and close diverge from Monday's ride-along.
30-minute readout with your ops leader. First patterns identified. Preliminary margin gaps quantified. Week 2 plan locked.
By the end of Week 1, our engineer knows your operation better than most consultants do after a month — because they were in the truck, on the phones, and in dispatch, not on a Zoom call reviewing a spreadsheet.
We don't just optimize techs. We map and standardize every revenue-critical handoff in your operation — because the call center and the truck are the same P&L.
Every call, booking, follow-up, and membership touchpoint — standardized and measured.
Every diagnosis, quote, close, and attach — consistent across every tech and branch.
Not a generic AI tool. Not a remote report. A forward-deployed engineer who deploys field service automation — AI call analysis, dispatch optimization, predictive pricing guardrails, and drift detection — built on your specific data, then measures it until the gains compound.
Our engineer embeds with your team, pulls data, rides along, listens to calls, and maps every revenue leak.
Top-performer knowledge becomes a system — field and back of house — with guardrails and standards.
Drift detection goes live across the full operation. Every metric tracked against baseline.
Connects to CallRail or ServiceTitan Phones Pro, transcribes and scores every inbound call against your top-CSR patterns. Shows booking rate by rep, missed objections by call type, and follow-up gaps by job category. Not averages — your specific CSRs, your specific call volume. See the CSR booking rate benchmark.
Analyzes which techs in your roster perform best on which job types, where callbacks originate by assignment pattern, and how routing decisions affect your specific margin profile. Not industry benchmarks — your dispatch data, your tech roster, your job mix. Skill-match rules built from your outcomes, not guesswork.
Real-time pricing guidance surfaced inside your existing ServiceTitan, HCP, FieldEdge, or Jobber workflow — no new login required. Trained on your pricebook, your job types, your historical close rates. Flags quotes that deviate from established ranges before they’re sent. Your techs keep working exactly as they do today.
AI monitors GM per job, callback rate, CSR booking rate, and follow-up completion every day — across your specific FSM data. Flags drift against your measured baseline before it hits the monthly close. Automated follow-up sequences trigger from FSM job status changes with zero manual handoff. See the full field service automation stack.
| Status Quo | Consulting | Point AI Tools | Spaid | |
|---|---|---|---|---|
| Scope | Siloed: field or phones, never both | Whatever they specialize in | Single function | Full operation: front office → dispatch → field → follow-up |
| Knowledge | Tribal, in people's heads | In a binder, on a shelf | Generic models, not your operation | AI graph built from your data, your people |
| Measurement | Monthly P&L (too late) | Before/after snapshot | Usage metrics only | Weekly drift detection, real-time guardrails |
| Stickiness | Depends on key people | Leaves when project ends | Adoption fragile | System stays, measures itself, improves |
| Time to value | N/A | 6–12 months, maybe | Unclear | Full-operation audit in 30 days, deployed in 60 |
Our Full-Operation Audit (Days 1–30) maps every revenue leak — field and back of house. If we don't identify at least $200,000 in recoverable annual revenue, we refund Phase 1 in full. You keep all audit deliverables.
After kickoff, we ask for about 30 minutes a week of your ops leader's time.
We'll start with a recent export or sample call data from your FSM and call system, show you the biggest leaks, and scope the engagement. Full access happens only if you proceed to the audit. If the numbers make sense, we start within 14 days.