Custom AI automation: what we build, and what we do not
A single automation or several, built around the tools you already use. No price until we know the scope.
Quick answer: custom AI automation for business means an agent, a workflow or a report built for one job in your company, connected to the tools you already use. It often follows the AI audit, but you can also ask for a single automation on its own. Each build is quoted once we know the scope, and a person checks anything an agent sends to a customer.
Most of what gets called automation is a generic tool, built for every business at once and bolted onto yours. Custom work is the opposite: one agent, workflow or report at a time, built to fit how your team already works. Nothing ships that you do not understand, and nothing reaches a customer that a person has not approved first.
We do not publish a build price on this page, because every build is different: a workflow that moves data between two tools is a different job from an agent that holds a conversation with a customer. What stays the same is how we get to a number. We look at the task with you, agree the scope in writing, and quote it before anything is built.
What counts as custom AI automation?
If it was built for your business, to fit a task you actually have, it counts as custom. A tool you install from a marketplace, built the same way for every buyer, does not, even if it uses AI. The difference matters because custom work can be scoped exactly to the people and the tools you already have, instead of asking you to change how you work to fit the tool.
That also means custom automation is not one product with one price. A workflow that files a document in the right folder is a small job. An agent that holds a full conversation with a caller and books an appointment is a bigger one. Both count as custom work, and both get scoped the same way, on a call, before we quote anything.
- Built for one task you already do, not a generic use case picked off a list.
- Connected to the tools you already use, so there is no new system for your team to learn.
- Scoped and quoted after we see the task, not sold as a fixed package before we know what you need.
What do we build: agents, workflows and reports?
Three kinds of things, each built for the job in front of it.
| What we build | What it does |
|---|---|
| Agents | Agents for customer support, lead qualification and internal research. They answer, ask the next question, and hand off to a person when the conversation needs judgement. |
| Workflows | Workflows for data, documents, approvals and fulfillment. They move information between the tools you already use, so nobody copies it by hand between systems. |
| Reports | Reports that show what each automation saves, in time and in money, so you can check the number instead of taking our word for it. |
How does a build follow the audit, or stand on its own?
Most builds start after the AI audit, once the written plan ranks what is worth automating first. You do not have to start there. If you already know the one task that costs you the most time every week, you can skip straight to a build.
| Path | What happens first | When it fits |
|---|---|---|
| Audit, then build | A written plan ranks every task by how fast it pays back, then we build the top ones. | You do not yet know which task to fix first, or you want the full picture before you commit. |
| Build only | We scope the one task on a call and quote it as its own project. | You already know exactly what you want automated. |
What are the guardrails on every build?
The same three rules apply whether you come from the audit or straight to a build.
- Agents draft. A person on your team approves anything that reaches a customer.
- We build around the tools you already use, so there is no new dashboard for anyone to learn.
- Nothing is bundled. You can stop after one automation, or after the audit, with no further commitment.
When should you not build custom automation?
A build is not always the right next step. Three signs it is worth waiting.
- The task happens rarely. A once-a-month task rarely pays back what a build costs to run.
- The task needs judgement every time. Forcing it into a fixed process tends to raise risk instead of cutting it.
- You are not sure which task to fix first. Start with the AI audit instead of guessing, so the plan ranks the options for you.
What have we built before?
Every project is custom, but two examples show the shape of the work: one built around a conversation, one built around data moving between systems.
An AI phone receptionist answers every call, qualifies the caller and books the appointment. See the example.
Automated lead management captures, qualifies and follows up with leads across every channel. See the example.
Every build is scoped on a call, not sold off a list. See all of our services, or book a free call to talk about yours.
Frequently asked questions
What is custom AI automation?
Custom AI automation is an agent, a workflow or a report built for one job in your business, connected to the tools you already use. It is not a generic app sold the same way to everyone. Most builds follow an AI audit, but you can also ask for a single automation on its own.
What do you build?
Three kinds of things: agents that answer and qualify customers, workflows that move data and documents between your tools, and reports that show what each automation saves. Each one is built for your business, not sold off a shelf.
Do I need an AI audit first?
Not always. The audit helps when you do not yet know which task to fix first, and it ranks every option in a written plan. If you already know the one task you want automated, you can skip the audit and ask for that build directly.
How much does a custom build cost?
Each build is quoted per project, once we know the scope. We do not publish a build price because the work varies too much from one business to the next. You get the number before anything is built.
Do I have to replace my current software?
No. We build around the tools you already use, whatever they are. The goal is one more working piece connected to your existing stack, not another dashboard or subscription for your team to manage.
What happens if an automation gets something wrong?
AI drafts, a person approves. Nothing reaches a customer until someone on your team has checked it, and you can always see what the automation did.