An AI software engineer for trades and field-service companies.
Your online quote form, booking page, pay-online page or customer login is part of how you win and keep jobs. An AI engineer looks after it and a separate QA agent grades every change, and anything that falls short of the grade you set goes back to the engineer.
Custom Permits, in numbers from their case study
180+
permit types handled, across all US states and Canadian provinces
6
Teammates running for them around the clock
700%
more Google impressions in three months, from their SEO Teammate
On their customer portal, the agent proposes and tests changes and a QA agent grades every code change before it goes to your branch rules.
You run a field business, not a software team.
Landscapers, exterminators, tree-care crews, builders and similar service companies often run a website with intake forms, online payment or a customer login. Someone built it once. When it needs a change, you wait on an agency or hope an employee has time.
Associates AI puts an Engineer Teammate on that code, with a separate QA Teammate reviewing its work. You ask for changes in plain English, such as a new service area on the intake form or a fix to the booking page, and you approve each change before it goes live.
The software work is done on a server that is yours alone, in your own code repository. If you have no repository yet, that is the first thing to set up on the call.
An engineer and a reviewer, on a server that is yours.
An engineer for the software you already have
The Engineer Teammate works in your repository on a server that is yours alone. It fixes bugs, makes the changes you ask for and opens a pull request with its test plan.
A separate reviewer
A QA Teammate that did not write the change reviews it. The engineer has to answer every finding.
A QA agent grades every change
Changes that fall short of the grade you set are sent back to the engineer. You do not need to read code to see what changed and what is still uncertain.
One flat price
$100 a month for any number of people. It includes one Standard Small server and 20 GB of storage. Model usage is billed at provider list rates.
How a change gets reviewed.
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1
You ask
Describe the change in plain English: a bug, a new field, a wording fix. The Product Teammate turns it into numbered acceptance criteria you can read and correct.
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2
The engineer builds it
It writes a test that fails for the stated reason, then makes it pass, and opens a pull request with the command output.
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3
Greenlight grades it
A separate QA reviewer grades the pull request 1 to 6 on a fixed rubric. Greenlight approves only at the grade you set, and findings come back to the engineer.
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4
Short of your grade, it goes back
A change that falls short goes back to the engineer. Your branch rules still decide the merge, and you get a plain-English summary and the list of open questions.
See Greenlight in detail → · See four real trails from our own repository →
You add a new service area and the intake form needs to know about it.
An illustration of the process, not a Custom Permits story.
A common request that means a call to the agency and a wait for a slot.
- 1.You describe it: customers in the new area should be able to pick it on the intake form, and the office should be notified. The Product Teammate turns that into numbered acceptance criteria you can correct.
- 2.The Engineer Teammate writes a test that fails because the area is missing, adds it, and opens a pull request with the command output.
- 3.The QA Teammate reviews the pull request and Greenlight grades it. If the notification was missed, the finding goes back to the engineer.
- 4.You read the plain summary and the open questions, then approve. The change goes live.
The request, the test and the review stay on the pull request, so the next change starts from a record rather than from memory.
Pro, priced at list.
Pro is one flat price for any number of people and includes one Standard Small server and 20 GB of storage. The table shows the engineering-lane example from the pricing page: Performance Medium server, included credit applied.
| Pro plan, any number of people | $100/mo |
| Server: Performance Medium, 2 vCPU / 8 GB | $124/mo |
| Included server credit: one Standard Small server | −$71/mo |
| Disk beyond the included 20 GB: 0 GB | $0/mo |
| Model usage | Billed at provider list rates, depends on volume |
| Fixed monthly before model usage | $153/mo |
Cost ceiling
Model usage draws from a prepaid account balance. With automatic top-up off, your teammates stop when the balance runs out instead of running up a bill. With it on, you choose the threshold and the top-up amount.
Find out whether an AI engineer fits your business.
Thirty minutes. We look at what you have, tell you plainly whether an AI engineer fits it, and show you how a change gets reviewed.
Book a 30-minute look