Service
AI workflow automation and software integration
We connect the software you already pay for and automate the admin work between it. AI handles the steps that need reading or judgment, and ordinary code handles the rest.
Where it helps
Admin work worth automating
Our founder managed projects in real estate development and oil and gas before moving into technology, so we start from how the work actually runs.
Construction and development
Quotes, change orders, subcontractor invoices and permit paperwork, matched to the right job and entered once.
Oil and gas services
Field tickets, timesheets and compliance documents pulled into your accounting and job-costing systems.
Professional offices
Client intake, document requests and follow-up emails, drafted for a person to check and send.
Any business with a busy inbox
Incoming requests sorted, summarized and sent to the right person with the details already filled in.
Worked example
Subcontractor invoices into QuickBooks
A general contractor's subcontractors email PDF invoices, and the office types each one into QuickBooks Online. Here is how we would connect the systems they already use.
The business keeps its inbox, QuickBooks and job list. Staff check bills instead of typing them, and the system catches duplicates and over-contract amounts that are easy to miss by hand.
This is an illustration of a typical project, not a past client.
- 01
Collect
A shared mailbox picks up each new PDF invoice through the Gmail or Microsoft 365 API.
- 02
Read
An AI model pulls out the vendor, invoice number, date, amounts, GST and job reference. When the job isn't stated, it matches by site address or PO number.
- 03
Check
Ordinary code confirms the vendor exists, the invoice hasn't been entered before, and the running total stays within the subcontract value.
- 04
Draft
A draft bill is created in QuickBooks Online, coded to the right vendor and job, with the PDF attached.
- 05
Approve
The office manager reviews the bills that are ready and anything that was flagged. Nothing is paid until a person approves it.
- 06
Record
Every step is logged, so anyone can trace an invoice from the email to the approved bill.
What we build
Four kinds of work
Software integrations
We connect your CRM, accounting, scheduling and email systems through their APIs, so data moves between them without retyping.
Document processing
We read invoices, purchase orders, intake forms and emails, extract the fields you need and flag anything uncertain for review.
AI agents
Agents handle multi-step tasks such as triaging requests or preparing drafts. You decide which actions need a person to approve them.
Custom software
When no existing product fits, we build a small internal tool around the way your team works.
Choosing a first project
What makes a good candidate
- It happens often enough to cost real staff time.
- The work follows a recognizable pattern, even with some exceptions.
- The information is available in digital form.
- A mistake can be caught before it reaches a customer.
Terminology
What about an AI operating system?
Some vendors use "AI operating system" or "AI OS" for a layer that connects a company's software, data, workflows and AI agents. It doesn't replace Windows or macOS on your computers.
The idea is useful, but the term has no settled meaning. We build toward it one workflow at a time, and each piece has to prove its value before the next one starts.
Common questions
How does a project start?
With a conversation about the problem. We then build one small workflow on your real systems, so you can judge the result before committing to more.
Do we have to replace our current software?
Usually not. Most of this work connects to the applications you already use. We check what each one allows before proposing anything.
What if one of our applications doesn't have an API?
There are often other routes, such as scheduled exports, email, direct database access or browser automation. We test the route early, because it affects what the system will cost to run and maintain.
Will the AI make mistakes?
Sometimes, yes. We design around that with validation rules, confidence checks and human approval on any step where an error would matter.
Does this have to use AI?
No. Ordinary code is cheaper and more predictable when a task has fixed rules. We use AI only for the steps that involve reading or judgment.
Have a process that eats up staff time?
A short description is enough. We'll reply with whether we can help and what a sensible first step would be.