Services
AI automation services that run inside your existing software
Most companies that say they "use AI" mean someone has a chat tab open. The dispatcher still checks the portal. The bookkeeper still keys the invoice. The two systems that matter still do not talk. We fix that: AI automation built into the software you already run, with a person approving anything that touches money, ranked by what it does to your P&L.
Illustrative example: planning and implementing improvements to everyday operations.
The gap between trying AI and running on it
The chat window is not the transformation. It answers questions; it does not do the work. The work lives in your TMS, your field-service app, QuickBooks, your ERP, your inbox, and the portals your customers and vendors make you use. Until AI can read from those systems and write back to them, it is a smarter search box.
What we see in most operations is the same three things. A person re-keys data from one system into another because nobody connected them. A person checks a website or an inbox on a schedule because nothing watches it for them. And the owner cannot get a straight answer about margin, cash, or on-time rate without someone building a spreadsheet by hand.
None of that is a model problem. It is an integration and workflow problem with an AI layer on top. That is what AI automation services should mean, and it is what we do.
Three phases, one owner
Prioritize, build, operate. Each phase ends with something you keep and a decision you make.
1. Prioritize.
Two days at your operation. We walk the workflows with the people who do them and score every candidate by value and risk.
You keep: the ranked roadmap and a business case for the first initiative.
The gate: you choose the first build, or you stop here with the roadmap. Either is fine.
2. Build.
One workflow at a time, quoted as a fixed fee before work starts, with acceptance tests in writing. A person approves anything that moves money or reaches a customer until trust is earned.
You keep: the code, the data, the accounts, and a trained team.
The gate: the acceptance tests. If the first build misses them, its fee is waived, and you keep it either way.
3. Operate.
The build runs inside your systems. We watch it, respond when a vendor changes something, and report each month on what ran and what needed a person.
You keep: everything, whether you keep us or not.
The gate: every twelve months, the managed plan is yours to renew or end. The next build starts when the roadmap says so, not before.
Each build earns the next. Most companies get three or four that matter, in the order the P&L says.
AI automation services, by function
We work function by function, and every workflow is named with the systems it touches and the P&L line it moves. If we cannot name the line, we do not build it.
Accounts payable and receivable. Invoice capture and coding from email and scans; three-way matching against purchase orders; AR reminder sequences that escalate to a human at your threshold; cash application. Systems: QuickBooks, Sage, NetSuite, your bank feed, email. P&L line: back-office hours, days sales outstanding, late-payment fees, duplicate payments.
Dispatch and status updates. Check calls, ETA updates, portal and email status to customers, exception flags on late loads or late jobs. Systems: TMS (TruckMate, McLeod), FSM (ServiceTitan, Jobber, Housecall Pro), telematics (Motive, Samsara). P&L line: dispatcher hours per job, on-time rate, the accounts you keep because reporting was clean.
Intake and scheduling. Reading inbound requests from phone, email, and web forms; creating the job or load; proposing a slot; confirming with the customer. Systems: phone system, FSM or TMS, calendar. P&L line: booked jobs per inquiry, response time, front-desk hours.
Quoting. RFQ-to-quote from your rate tables and job history, with review before it goes out. Systems: email, CRM, pricing sheets, ERP. P&L line: quote turnaround, win rate, margin on quoted work.
Reporting and visibility. The weekly owner report: revenue, margin by lane or job type, deadhead or drive time, AR aging, on-time rate, pulled from every system into one page. Systems: all of the above. P&L line: the decisions you make a week earlier because the number was in front of you.
Where the workflow needs judgment, reading a document, watching a portal, deciding what to do next, we build an AI agent. Where it needs plumbing, we build an integration. What an AI agent is and the twelve we assess for →
A person stays on every decision that costs money
Automation earns trust in stages. We build it that way on purpose.
First, a shadow period: the automation runs, a person keeps doing the job, and we compare. Then a parallel run: the automation does the work and a person reviews before anything leaves the building. Then production, with approval steps on the decisions you name: a disputed invoice, a quote above a threshold, a customer-facing message with a problem in it, anything that moves money.
Every action is logged. You can see what the system did, what it saw, and who approved it. That is not overhead; it is what makes the owner comfortable turning it on.
Systems we work inside
We do not replace your software. We connect to it.
Trucking and logistics: Trimble TruckMate, McLeod, Vizion, Motive, Samsara, MacroPoint. Trades and field service: ServiceTitan, Jobber, Housecall Pro, Procore. Finance: QuickBooks Online and Desktop, Sage, NetSuite, Bill.com. Professional services: Clio. Everyone: Microsoft 365, Google Workspace, your phone system, and the portals your customers and vendors run.
If your system has an API, we use it. If it does not, we work from its exports and reports and tell you up front what that limits. How integrations work →
How we decide what to automate first
We do not start by building. We start with a two-day AI Readiness Assessment at your operation.
Day one, we walk the workflows with the people who do them. Day two, we score every candidate on two axes, P&L impact and risk, and hand you a ranked backlog you keep whether or not you hire us again. Then we quote the first build: one eligible workflow, with acceptance tests in writing. If it misses them, the build fee is waived.
The assessment starts at $10,000 and is credited once against your first build.
What it costs
- AI Readiness Assessment: from $10,000, two days on site, credited once against the first build.
- Build workstreams: fixed fee, from $10,000 each, sized by systems touched, data quality, and number of integrations. Quoted before work starts, not by the hour.
- Managed AI: from $1,200 per month. Monitoring, fixes when a vendor changes something, engineering hours included. Priority-one response in four business hours on the Managed plan.
Prices verified September 2026. Full detail on the pricing page.
Why Vorsa Logic
Business goals first. Every workflow is mapped to a P&L line and ranked by measurable return and risk before we write code. If a plain integration beats an AI agent, we tell you.
Built into what you already run. No rip-and-replace. Your TMS, FSM, and accounting system stay the systems of record.
Yours to keep, ours to run. You own the code, data, and accounts. We stay on with a managed plan so it keeps working when a vendor or a portal changes.
Founder-built by Jonathan Klein and Chip Ray, based in Houston. Insured: cyber liability, technology E&O, and general liability.
Proof
A Houston trucking company tracked 600 to 700 import containers a month by checking port and steamship-line websites by hand. We built a monitoring agent inside their TMS (TruckMate), their tracking provider (Vizion), and Microsoft Teams. Dispatch gets a daily digest and alerts when a last-free-day moves; exceptions go to a person. They own the system and keep us on a Managed plan to fix it when a port or vendor changes something. See it in the trucking and logistics page →
What happens after go-live
Software that talks to other companies' systems breaks when those companies change things. That is the job, not a surprise. Our managed plan monitors the system, fixes it when a vendor changes an API or a portal changes a page, and includes engineering hours each month for the next improvement. How managed AI works →
Frequently asked questions
Automation follows fixed rules: when X happens, do Y. An AI agent handles the parts that need judgment: reading an unstructured document, deciding which last-free-date to trust, drafting a reply. Most real workflows need both. We build the rules where rules work and add an agent only where judgment is required, because rules are cheaper and easier to trust.
The first build is quoted with its own schedule, scoped to one workflow so it can go live in weeks, not quarters. The shadow and parallel-run periods add time before you turn off the manual process, and that time is deliberate.
It usually is. Part of the assessment is finding out how messy, and the first workstream often includes a data-cleanup step. We tell you what the mess limits before you commit. We do not build a forecast on numbers nobody trusts.
Almost never. We build inside and around what you already run. If your core system is the real problem, we will say so, but that is rare. The problem is usually what sits between your systems.
The assessment starts at $10,000 and is credited once against the first build. Build workstreams are fixed-fee, from $10,000 each, quoted before work starts. Managed plans run $1,200 to $2,200 a month.
Have a workflow someone does by hand every day?
Book a two-day assessment. You get a ranked list of what is worth automating, scored by P&L impact and risk, and a fixed-scope proposal to build the top one.
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