AI operations for multi-brand home services

Make every team operate like your best one

SpireField AI reads your ServiceTitan, payroll, accounting, and expense-card data. It tells every team what to do today to increase revenue, and takes the actions with your approval. More first-time fixes. More replacement wins. Higher profit per truck roll.

SpireField AI · Actions today

Actions today

Owner / exec view
Reading last night’s data and building today’s actions…
Reads acrossServiceTitanADPSageQuickBooksRamp

🧠 It runs on your best people’s judgment, and it gets sharper. Learn more →

For managers · Actions Today

Every morning: taking action to increase revenue

Your field teams follow different standards. Actions Today runs every team like your best manager would.

Instead of spending the day reacting to whatever comes in, managers start it playing offense. Targeted actions for specific jobs, techs, and dollars to grow the business, ready before the first truck rolls.

Today

Prep replacement quotes for Stubbs and Zamora, before the tech knocks

$9,424–$18,848 at stakeOwner: You / sales manager
Edit
This week

Escalate Cliff Villareal, 3 visits in 17 days, to a replacement conversation

$9,000–$9,500 at stakeOwner: Brand GM
Edit
This week

Pair Nick Foss with a senior tech (5 callbacks this month)

Each callback costs ~$133 in labor with zero revenue. At his rate that's ~$665/month in waste, plus customer churn risk.Owner: Service manager
Edit

Honest about gaps: No warranty claim data loaded. Can't check warranty recovery rate · No fleet/GPS data. Fuel cost per job not calculable

claude-sonnet-5 · $0.22 per run · replay of a real run on sample data

Ask a follow-up. The AI keeps the full context

For techs · Job Predict

Every job, pre-screened before the truck rolls

Your technicians go into homes without guidance. Job Predict tells them the fix, parts, price, and replacements, before the truck rolls.

New techs perform like veterans sooner, and techs who succeed stay longer.

Job Predict: Carrier Central AC

tomorrow’s board

Customer reports: "AC blowing warm again." 2011 unit, third service call this season.

Likely diagnosis

50%
Run capacitor failure
25%
Compressor wearing out
15%
Refrigerant leak recurrence
10%
Condenser fan motor

Parts to have on hand

50%Dual run capacitor (45/5 µF)
15%R410A refrigerant (2-3 lb)
drafts the supply-house order. See it in action below

Price range

$349 – $890

from your own price book

Replacement flag

⚠ 3rd repair this season on a 2011 unit, about $1,900 spent. Take the $9,800 replacement quote to the door

🧠 Encoded rule applied to this job

Any customer with 3+ service calls in 30 days on the same equipment should be flagged for a replacement conversation, not another repair.

Service manager weekly huddle, May 2024 · cited on 8 jobs this month

claude-sonnet-5 · $0.10 per run · replay of a real run on sample data

For everyone · Ask Anything

Access and use your data with a simple chat

Your data is hidden across complex dashboards. Ask Anything gives you the answers to get more profit.

This makes it easy to use and grow. Across ServiceTitan and every major system you run, no training required.

Summit Home Servicessample company

ServiceTitan + ADP payroll + Sage accounting + Ramp cards

Ask anything about your business…Send

Sample questions. Tap one to see it answered

If your team can send a text, they can use this. Use right away, not after months of onboarding. ServiceTitan stays your system of record. This is your system of intelligence. No report builder, no new screens for your team to learn.

Every action is specific, sourced, and priced in dollars

You approve.
The AI does the work.

SpireField AI surfaces specific actions to execute: the exact job, the exact tech, the exact part number, the dollar value, and who owns it. You approve, and the AI carries it out.

Drafted parts order: tomorrow’s board

Drafted by the AI

Cascade Supply Co. · Order desk, Branch 12

Account #4471 · Will-call pickup under “Summit, Mike R.”

Run capacitor 45/5 µF 440V ×2

median of 39 of your invoices

$80.00 ea

Contactor, 2-pole 30A ×1

median of 78 of your invoices

$85.00

Condenser fan motor, 1/4 HP ×1

no invoice match found

TBD, desk will quote

Subtotal

$245.00 + 1 line to be quoted

EditReject

Drafted by the AI. Sent by software. Approved by you, every time.

Send the parts order

Drafted PO emailed to the supply house: part numbers, quantities, account number, will-call pickup. The Approve demo above is the real flow.

The right part on the truck = the job done in one visit, not two.

Follow up on every stale estimate

The AI finds the quotes going cold and drafts a personal follow-up to each customer: their specific quote, their equipment, the season. Approve the batch → sent.

Quoted work that never closed is the cheapest revenue there is.

Renew every expiring membership

Drafted renewal notes built from each customer’s own history, plus winback offers to customers with aging equipment you haven’t seen in 18+ months.

At the sample company: a $56K/year membership gap between best and lagging brand.

Keep every truck stocked and tracked

Stock levels computed from what each tech actually uses. Restock orders drafted weekly → approve → sent, and truck inventory stays current. No scanning, no counting.

A pain every shop knows, solved from the paperwork you already generate.

Flag the dispatch board

“Reassign job 9914 from Nick Foss to Tom Brandt: double-booked, and Foss is at 5 callbacks this month to Brandt’s zero.” One tap applies it in ServiceTitan.

At the sample company: one tech’s callbacks were ~$665/month in wasted labor.

Replacement quote ready before the tech knocks

Draft estimate written onto the job in ServiceTitan, built from the customer’s own repair history. What they’ve already spent does the selling.

At the sample company: the average replacement deal is $9,424.

Plus: 5:30 AM pre-job briefings for every tech, warranty claims on parts that failed in-warranty, coaching packets for high-callback techs, context-aware confirmation calls. Every one behind the same approve button.

You approve the policy once, “yes, always order tomorrow’s parts the night before,” and the AI executes every instance.

What one overnight run found

Every number below came from the examples you just saw. One pass over the sample company’s data.

$9.4K–$18.8K

of replacement opportunity on tomorrow’s board, flagged in time to prep the quotes

$25,300/mo

replacement close-rate gap between the best and middle brand

$18,700/mo

gross-margin gap between the best and lagging brand, with the two causes named

$56K/yr

membership-revenue gap between the best and lagging brand

The same overnight pass runs on your numbers in week one.

Messy data? Missing fields? That’s normal, and it’s fine.

Most teams don’t fill in every field, and this tool was built for exactly that.

No required fields

It reads whatever columns exist and works from what’s there. Nothing breaks because something wasn’t entered.

Runs on the records you already create

Every dispatch and every invoice generates data automatically, and most of the answers above run on those records alone.

Honest when something’s missing

When the data can’t answer something, it says “couldn’t check, not in the data” instead of guessing. You saw it on the actions list above.

It runs on your best people’s judgment, and it gets sharper

Your strongest technicians and service managers know things that aren’t written down. SpireField AI captures that from tech trainings, ride-along recordings, meetings, and expertise you select. It then encodes that expertise into the AI agent and applies it to every job, at every brand. You saw one on the Job Predict card above.

1 · Captured

“Every time Lennox tech support says board, I check the inducer first. Eight out of ten times that’s all it is.”

🎙 Ride-along with Mike Chen (senior tech), June 2024

2 · Approved by you

The quote becomes a proposed rule. You accept, edit, or reject. Nothing changes behavior silently.

✓ Accepted

3 · Applied & cited

The $312 inducer ranked first, the OEM’s $1,480 board last, because of this rule. Cited on 12 jobs this month.

And it grades itself: every prediction is checked against the actual close-out in your next export. No one clicks right or wrong. Misses become proposed rules. The system gets sharper from its own mistakes.

Walk through the product →

Same standard, every brand

You bought ten companies. Now you can see which ones are leaving money on the table, and exactly where.

Basin runs a 45.7% gross margin to Ridgeline’s 60.5% on the same work.

The gap is parts cost (29% higher per job) and OT-driven labor. Closing it is worth ~$18,700/month in gross profit.

Ridgeline closes replacement leads at 35.7%. Clearwater: 26.5%.

At Clearwater’s lead volume that’s ~$25,300/month left on the table. A close-process gap, not a lead-volume gap.

Same playbook rules, applied at every brand. Same data, read the same way. The gaps stop being anecdotal and start being specific, with a number and an owner attached. And as your teams see this drive their daily work, the data gets better on its own, because it’s the first time filling in a close-out field comes back as something useful the next morning.

See it on your own numbers

Runs on the exports your systems already produce. One saved ServiceTitan report, dropped in. Live in week one, no integration.

Get in touch

The demos above replay real product runs on a fictional company’s sample data.