ClientWeb · Paid
Contractor demand engine
Site, local search, paid and routing in one retained system, reported on booked jobs.
Home services
AI development for home services
Home services businesses lose jobs on the phone. Calls ring out after hours, office staff juggle dispatch and booking, and techs in the field cannot reach job history fast. An AI agent helps only if it can see the schedule, book into it correctly and hand off cleanly when a caller needs a person.
We build voice and text agents connected to your field service management system, estimate and quoting assistants, mobile tools for techs, and the call and booking data that shows which jobs the system actually produced.
Talk to an engineer →Scope in one week. You own the repo from commit one.
Start a project
Step 1 of 5
Got it. An engineer is reading your brief.
You will hear from us within one business day, usually sooner. If it is urgent, email t@moher.ai.
Problems we solve in home services
- After-hours and overflow calls go to voicemail and the job goes to a competitor.
- Booking requires a human to check the schedule, zones and tech skills.
- Estimates take days because the office rebuilds them from scratch.
- Techs arrive without job history, photos or equipment details.
- Call recordings and job notes sit unused instead of feeding training and QA.
- Text and call automation runs without checking consent rules.
What we build
Systems we build for home services
01
Voice and text booking agent
Answers calls and texts around the clock, qualifies the job, checks real availability in your FSM and books it, with a warm transfer when needed.
02
Estimate assistant
Drafts estimates from photos, notes and your price book, flagged for office review before they go to the customer.
03
Field tech mobile app
Job history, equipment records and manuals searchable on site, with voice notes turned into structured job records.
04
Call QA and summaries
Transcription, summaries and scoring of calls against your booking script, written back to the job record.
05
FSM and dispatch integration
Two-way connections to field service management, dispatch and CRM systems so the AI reads and writes the same schedule your team uses.
06
Follow-up and review requests
Post-job messages and maintenance reminders sent on rules you set, with consent checked before every send.
Shipped in this industry
Running in production
Client names stay under NDA. The shapes do not.
Home services questions
Something else? Email t@moher.ai and an engineer will answer it.
Which field service tools do you integrate with?
The common field service management and dispatch platforms, through their APIs and webhooks. Where an API is limited we build a sync layer and say so up front.
Will callers know they are talking to AI?
We recommend disclosing it, and design the agent to transfer to a person on request or when a call goes outside its rules.
How do you handle call recording and texting rules?
We design for TCPA consent on texts and outbound calls and for call recording consent rules in the states you operate in, and work inside your legal review. Consent status is checked before any automated message.
Can it handle emergency calls?
It can identify emergencies from rules you define and route them to the on-call tech immediately rather than booking a slot.
What does a first engagement look like?
Usually the booking agent on after-hours calls first, then overflow. Four to eight weeks to production.
Tell us what you need built
Four quick questions and an email. An engineer reads every brief and replies within one business day with next steps, and a written scope follows within a week.
- Written scope and price within a week
- Production deploy by week three
- Your repo and cloud from the first commit
- Senior engineers only, no account managers
Start a project
Step 1 of 5
Got it. An engineer is reading your brief.
You will hear from us within one business day, usually sooner. If it is urgent, email t@moher.ai.