Industries
AI answering service and expertise capture for contractors
Two things limit how much work a service business can take on: the calls it cannot answer and the people it cannot clone. We build inside the tools you already run: an answering service that books the job, and a knowledge system that keeps what your best technicians know.
If this sounds like your shop, you're in the right place
Calls you never hear about, because nobody could pick up and the voicemail went unheard until the next morning. After-hours emergencies routed to a personal cell. One technician who knows every panel at your biggest account, and a second visit every time someone else is sent. New hires who take a season to become useful because the real procedures were never written down. An estimate approved on a Tuesday that becomes an invoice the following week because it passed through three people and two systems. Photos in CompanyCam, hours in the FSM, receipts in Ramp, payroll in Gusto, and a bookkeeper reconciling all four by hand at month end.
We work with owners to decide which matters more right now. An AI answering service that books the job straight into ServiceTitan, Jobber, or Housecall Pro. A knowledge system that captures what your best technicians know about the sites and the equipment. Back-office agents that turn the estimate into an invoice without a week in between.
For industrial firms, the same shape with different names: quotes built from drawings by the one engineer who knows how, project status that lives in five heads, and a team using six different AI tools with no rules about what goes into them.
None of this is a talent problem. Some of it is work that software should be doing inside the tools you already pay for. The rest is knowledge that lives in a few heads and needs to live in the company.
AI answering service wired into dispatch
A cheap AI receptionist app answers the phone and takes a message. That is where most of them stop, and a message is only slightly better than voicemail.
Ours is wired into your dispatch. It answers every call, asks the questions your dispatcher would ask, checks the customer against your FSM, and books the job into the right slot for the right trade and zone. It knows which calls are emergencies and transfers those to a person, on the schedule you set. It sends the confirmation text. Everything it does is logged in your system, not in a separate inbox.
What it handles on its own. New service requests, with the address, the problem, and the preferred window captured and the job created. Existing customers, recognized by phone number, with their history in front of the agent. Questions about hours, service area, and pricing ranges you have approved. Confirmations and reminders by text. Rescheduling.
What it hands to a person. Emergencies, on your definition, transferred to the on-call number. Commercial and multi-site inquiries. Complaints. Anything it is not confident about, which it logs with a transcript so the person picks up where it left off.
What it costs you to run. A fixed monthly amount, not a per-call fee, so the incentive is to answer every call. Booked jobs from calls that used to go to voicemail is the first number most owners ask us to measure.
Systems: your phone system, ServiceTitan, Jobber, or Housecall Pro, your calendar. P&L line: the jobs you book from calls you used to miss, and the front-desk hours you get back.
Expertise capture for the people who know the sites and the equipment
Every service business has them: the technician who knows which breaker the customer mislabeled, the coordinator who knows which vendor actually answers, the estimator who knows what a job at that plant really costs. When they are on another call, the work waits, gets repeated, or gets done wrong. When they leave, it goes with them.
We build a knowledge system that captures that expertise and puts it in front of the rest of the team. Your experts talk it through by voice or text, with photos from the site, and the system asks the follow-up questions and drafts the article: a site profile, an equipment procedure, a troubleshooting guide, a vendor profile, a client protocol. An accountable expert reviews and approves. Technicians and office staff ask questions in plain language and get an answer with the source behind it, in the context of the job or the work order. When there is no supported answer, it says so and routes the question to a person.
What it changes. Fewer repeat visits caused by missing site or equipment knowledge. New technicians productive in weeks, not a season. Fewer interruptions reaching the owner and the senior people. A business that is less dependent on any one person.
Proof. A Houston security, access-control, and IT services contractor came to us with undocumented site, equipment, troubleshooting, and supplier knowledge held by a few experienced people. We built the core of a knowledge system for them: an editor and library, voice and text capture assistants with gap tracking, versioning and publication, team and role management, and lookups into their job-management software. They tested it against real work and fed back defects and requests, which is what the parallel period is for. Full field rollout and continued content development are scoped separately, on their timeline.
Systems: your FSM or job-management software, Microsoft 365 or Google Workspace, your document store. P&L line: repeat visits, ramp time for new hires, senior hours spent answering the same question. How AI knowledge systems work →
Industrial automation, panel shops, and data centers
An industrial automation firm we work with builds control panels and does design work for data centers. Their bottleneck was not the shop floor. It was quoting from drawings, knowing where every project stood, and the engineering knowledge in a few heads.
What we build for firms like that: capture of PLC and engineering know-how into a searchable, permissioned knowledge base, the same pattern as above; quoting agents that read the drawing package and the bill of materials and draft the quote for an engineer to check; project status roll-ups that pull from the PM tool, the ERP, and email into one page for the owner; and governance across the AI tools engineers already use, so nobody pastes a customer's drawings into a public chatbot. P&L line: quote turnaround and win rate, engineer hours, the project nobody noticed was late.
The governance piece deserves a sentence on its own. Engineers will use AI tools whether or not the firm has a policy, and the useful ones are useful. The risk is a customer's drawing package or a proprietary control scheme pasted into a public model. The fix is not a ban. It is an approved set of tools with the right data terms, a short written rule about what goes where, and logging, so the firm can say yes to the tools and still answer a customer who asks where their drawings went.
The rest of the back office
Estimate-to-invoice. The approved estimate becomes the job, the completed job becomes the invoice, the invoice lands in QuickBooks, and the customer gets it the same day. Systems: FSM, QuickBooks. P&L line: days-to-invoice, cash.
AR follow-up. Reminders on the schedule your office manager would use, escalation to a person at your threshold. Systems: QuickBooks, email, text. P&L line: DSO.
The four-way reconciliation. The same Houston contractor ran jobs in Jobber, photos in CompanyCam, spend in Ramp, payroll in Gusto, and books in QuickBooks. We connected them so job costs, receipts, and hours land where they belong without a person copying. P&L line: bookkeeper hours, job-cost accuracy.
The weekly owner report. Booked revenue, completed revenue, margin by trade, AR aging, tech utilization, callbacks. One page, Monday morning. P&L line: decisions made a week earlier.
Driver and tech document capture. Licenses, certifications, insurance, and onboarding documents collected and filed, with alerts before anything expires. P&L line: compliance labor, the job you cannot staff because a cert lapsed.
Human review stays on anything that touches money or reaches a customer with a problem in it, until the agent has run in parallel long enough to earn your trust. The full list of back-office agents →
How a build runs at a contractor
The receptionist is a good example. Week one, we connect to your phone system and your FSM and build the agent against your real call flow: the questions your dispatcher asks, the zones and trades you cover, the slots you will let it book. Week two, it runs in shadow: it listens to real calls alongside your office and drafts what it would have done, and we compare. Then it takes the overflow and after-hours calls first, with every booking reviewed the next morning. Then it takes everything, with a person on the transfers.
A knowledge build runs on the same idea with different steps. One domain first, such as your top ten accounts or one equipment family. A small group of experts who own it, and capture sessions that fit around their jobs. Review and approval before anything is published. Then real questions from the field, with the misses investigated and the content corrected, before the next domain starts.
Nothing is switched off until the office manager says so. The same pattern applies to estimate-to-invoice, to the reconciliation, and to the owner report: shadow, parallel, production, with the numbers matched before the manual process stops.
Systems we work inside
ServiceTitan, Jobber, Housecall Pro, FieldEdge. QuickBooks Online and Desktop. Gusto, ADP. Ramp. CompanyCam. Procore. Microsoft 365 and Google Workspace. Your phone system, whichever one it is. If it has an API we use it; if it does not, we work from exports and tell you what that limits.
How we decide what to build first
It starts with a conversation about what the business needs to achieve: more booked work without more office staff, fewer repeat visits, a shop that runs without the owner on every call. Then a two-day AI Readiness Assessment at your shop. Day one, we ride along with dispatch, the office, and the field. Day two, we score every candidate on value, risk, effort, and readiness and hand you a ranked roadmap you keep, with a business case for the first initiative. Then we quote the first build against written acceptance tests. If it misses them, the build fee is waived.
The assessment is $10,000, credited once against your first build. Discuss your business priorities · Book your assessment
What it costs
- AI Readiness Assessment: $10,000, credited once against the first build.
- Build workstreams: fixed fee, from $10,000 each, quoted before work starts. A knowledge build is quoted in parts: the system, initial capture and curation, integrations, and ongoing stewardship.
- Managed AI: from $1,200 per month, with priority-one issues responded to within four business hours on the Managed plan.
Prices verified September 2026. Full pricing →
Why Vorsa Logic
Business goals first. Every agent has a P&L line before it has a design. The receptionist is ranked by booked jobs, not by how human it sounds.
Built into what you already run. Your FSM stays the system of record. Nothing lives in a separate app your dispatcher has to check.
Yours to keep, ours to run. You own the code, the content, and the accounts. We carry the pager.
Founder-built by Jonathan Klein and Chip Ray, based in Houston. Insured: cyber liability, technology E&O, and general liability.
What happens after go-live
Phone systems, FSMs, and accounting tools change their APIs, and knowledge goes stale as sites and equipment change. Our managed plan monitors every agent, responds when a vendor changes something, and includes engineering hours each month. Knowledge stewardship keeps the content current: a review queue, scheduled capture sessions, and stale-content checks. How managed AI works →
Frequently asked questions
A live service costs per call and takes a message. Our AI answers every call at once, books into your dispatch board, and costs a fixed monthly amount. Where a person is better, an upset customer, an emergency, a complex commercial job, it transfers to one. Many contractors keep a live service for overflow and let the AI handle booking.
ServiceTitan, Jobber, Housecall Pro, and FieldEdge, yes. Others with an API, usually. If yours has no API, we tell you what that limits before you commit.
It is built as a workstream, fixed fee, quoted before work starts, and usually at the lower end of our range. The assessment that scopes it is $10,000 and is credited once against the build. Managed plans run $1,200 to $2,200 a month.
In short sessions that fit around the work: a guided voice or text conversation, often from the truck, with photos from the site. The system asks the follow-up questions and drafts the article. The technician reviews and approves it later. Most experts find it easier than writing anything down, which is why the documents were never written.
It identifies itself as an assistant when asked and never pretends to be a person. In practice customers care that the call was answered and the job was booked.
You define what counts as an emergency and who gets the call. The AI qualifies, transfers to the on-call person, and logs the job. Nothing waits for morning.
We help you write the rules: what data can go where, which tools are approved, and how usage is logged. For industrial and engineering firms handling customer drawings, that governance is usually the first workstream.
Which would change your year first: the calls you miss, or the knowledge you can't clone?
Tell us what the business needs to achieve. If AI is part of the answer, the assessment gives you a ranked roadmap, a business case for the first initiative, and a fixed-scope proposal to build it.