AI MVP development studio
An AI MVP development studio for a product you can launch.
An MVP here means the smallest version a customer or a team can use next month. Shipfold Labs scopes that version, builds it, and puts it on its own URL. The studio works remotely, with teams wherever they are. The engagement is a fixed-scope sprint, then a retainer if the first version earns a second one.
What the sprint is for
Companies come to an AI MVP development studio when a slide deck has already outlived its usefulness. Someone has a job that a person does every day — sorting mail, drafting a first reply, checking a spreadsheet against a system of record — and they want software that does that job, with a model where a model helps and with a person still able to stop it. The sprint exists to put that software in front of a real user before the scope grows a second product inside the first one.
The first week is the cut. We write down the user, the one job the product does, and the list of things that wait. Internal tools, customer-facing apps, and LLM features all go through the same cut. If the launch cannot be described in a paragraph, the project is still too big and we say so before anyone writes code. That paragraph becomes the test at the end: a named person can finish the job on the public URL without a founder sitting next to them.
We do not staff a research lab, and we do not sell a model. Training a custom model, inventing a new agent framework, or promising “AI transformation” across a whole company is a different business. If the job is “add a chatbot to the homepage,” we will say so and suggest a narrower tool instead: one workflow, one screen, one way to see when the answer was wrong.
What you have at the end
The build uses a real stack and a real host. Third-party services sit behind an interface so the product runs before the production keys exist. Logs exist so a bad answer can be traced. Auth is real when the product needs an account, and a public page is real when the product is meant to be found. The deliverable is the source, the deployed URL, a short note of what was left out on purpose, and a list of the next slices in the order we would build them.
Afterword, the review tool for law firms, shipped that way and now lives at https://afterwordreviews.com. It asks for a Google review in English or Spanish, gives every client the same link, and keeps consent and STOP on file. It is the proof that “built and shipped by Shipfold Labs” means a product with its own domain, not a case study borrowed from somewhere else. The same shape fits an internal drafting tool or an automation that sits between two systems a company already pays for.
Launch is a public page, a way to hear from the first users, and a short list of what the following weeks should change. A retainer is how that list gets built. The sprint is how the first version exists. Starting prices stay on the homepage as “starting at,” because a number without a scope is a guess. The form stores the note. It does not send email by itself. You can also write hello@shipfoldlabs.com.
How this page fits the rest of the studio
If the question is how the weeks are spent, read build an AI product fast. That page covers the process. This one is the offer: a fixed-scope AI MVP, a URL, and a cut that is small enough to launch.
Questions
What do you deliver at the end of an MVP sprint?
A working product on its own URL, the source, a short note of what was left out, and a list of the next slices. It is software a customer or a team can use, not a slide deck.
How is an AI MVP different from a prototype?
A prototype proves a screen. An MVP here has auth or a clear public path, stored data, and a model call behind an interface that still runs when the API key is missing.
Can the first version include an LLM?
Yes, when the model does one job. Prompts, logs, and a fallback are part of the sprint. A general chatbot bolted onto a homepage is not.
Where can I see a product you shipped?
Afterword is the live example. It asks law-firm clients for Google reviews in English and Spanish. It is built and shipped by Shipfold Labs.