Scoping and a first working version
We write down what the product does, for whom, and what it must not do, then build the narrowest version that proves the hard part. If the hard part cannot be done well, you learn it early.
Products and tools
Custom AI development for the tool nobody sells.
Custom AI development for companies nationwide: new products and internal tools built on AI, with the software, the data, and the interfaces around the model, and the keys in your hands at the end.
The discipline
The model is the smallest part of the product. The rest is what we build.
Off-the-shelf AI tools answer general questions well and your specific one badly. A tool built for your question is still a product, and it needs a database, accounts, permissions, an interface people will tolerate at four in the afternoon, a way to recover when the model is wrong, and a way to tell. Custom AI development is building all of that around the model. We take it from a scoped plan to a working version on real data, then to a finished system, handed over, not licensed back to you.
What it includes
What custom AI development covers when the product has to be yours.
AI software development
An AI product is mostly ordinary software done well: accounts, permissions, background jobs, interfaces for web and phone, and connections to the systems you already run. We write it to be read and changed by the next developer, who may not be us.
Data pipelines and preparation
Products fail on the data before they fail on the model. We build the pipelines that collect, clean, label, and refresh what the model reads, and make them boring enough to run unattended.
Prompting, retrieval, and fine-tuning
Choosing between a prompt, retrieval over your data, and a fine-tuned model is a cost and quality decision, not a matter of fashion. We make it by measurement, keep prompts under version control, and define behavior by tests rather than assumption.
Interfaces and experience
A person meets the system in a chat, a form, a dashboard, or a button inside software they already use, and a product people avoid opening is not a product. We design for the moment the model is wrong, so the person stays in control.
Ownership and handover
Code, infrastructure, prompts, evaluation sets, documentation, and the keys to all of it are delivered in your accounts under your name. You may keep us on afterwards, and nothing in the system will require it.
The build
How AI product development runs here, and where you get to say no.
01
Scope
A short document covers the problem, the user, what the first version does, what it leaves out, and what it will cost. If the idea does not survive the writing, you find out before anything is built.
02
Prove
The narrowest working version goes on real data, in front of real users, early. It is often rough and never fake, and exists to find out what is true before the design is expensive to change.
03
Build
The full product arrives in short cycles, with something running at the end of each. You see the work as it exists, not as it is described, and the plan bends to what you learn.
04
Ship and hand over
We launch, with monitoring and support while the product meets its first real users. Then we hand over, with a working session for whoever will run it next.
Who we build for
Who hires an AI developer, and what they bring.
Owners, founders, and product leaders in nearly every industry, across the United States, come to us when they would rather own the result than rent it.
Small businesses
An owner arrives with a product idea that only makes sense now that the models exist, and no appetite for a long contract. We build the first version with them and say plainly when it is enough.
Mid-sized companies
A company wants the internal tool the vendors do not sell, built on records it has kept for years and never been able to question. No one else can buy it, because it exists nowhere else.
Large organizations
A product team with the mandate and the backlog needs the AI parts built without slowing the roadmap. We take the model layer, the evaluation, and the moments where the interface meets uncertainty, and leave the rest to the team that owns it.
Fair questions
What people ask an AI development company before a build begins.
Do we own what you build?
Yes. Code, prompts, evaluation data, infrastructure, and documentation sit in accounts under your name from the first day. The only terms we cannot sign over belong to the model provider and to any open-source library, and the scope names both. We write the handover as if you will never call us again.
Should we build a custom AI product or buy one?
Buy when a product does the job and your data is not what makes it valuable. Build when the value is in your data, your process, or something your customers cannot get elsewhere. We will say which, including when the answer is buy and the engagement ends there.
What do AI development services cost?
Each scope is priced in writing before work begins: a fixed price for a defined first version, or a clear rate for work that is open-ended by nature. We would rather quote the real scope than publish a range that fits no one.
What if the idea turns out not to work?
Then you find out at the proving stage, for the cost of a first version, with a written account of why and what would have to change. That is a good outcome. The expensive version arrives after launch, with customers watching.
Begin here
Describe the tool you cannot buy.
A sentence about what it should do is enough. It reaches the person who would build it, and the reply says whether it should be built.
Received
Thank you. We will be in touch.
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If it cannot wait, call 718.501.4294.