Define the problem. Then build it with AI.
Anyone can prompt their way to something that looks finished in an afternoon. PromptCraft picks up from there. We start by defining the target — what it needs to do, for whom, and how you'll know it's working — then take the complexity of delivery off your plate and build with AI against that spec. The outcome is held to a production bar, not a demo bar.
Definition first. AI second. Production always.
Most "AI problems" are actually specification problems wearing a prompt-shaped disguise. We fix the specification, then build.
Problem definition & specs
Turning a vague ask into a written spec — what it needs to do, for whom, and how you'll know it's working — before any prompt or line of code exists.
Design & build from scratch
No prototype to start from? We design the thing as well as build it — interface, flow and content — not just engineering on top of someone else's mockup.
Component-level AI build
Not one long prompt for the whole feature — each component is built against its own playbook, tuned from what's worked before, and reviewed like production code before it's trusted.
Evaluation & testing
Eval suites and regression tests so you know a change made things better, not just different, before it ships.
RAG & context design
Retrieval and context strategies that get the right information in front of the model without drowning it.
Model & cost review
An honest look at whether you're on the right model for the job, and where token spend is going to waste.
Cloud deployment & ownership
Built and supported on AWS, Azure or GCP — whichever you're already running on. Every component ships deployable, not just demo-ready, and the code is yours to own outright, no proprietary platform to stay locked into.
Team training
Hands-on sessions to get your own engineers defining problems properly and building with AI to a production standard.
Definition first, then AI — in that order, every time
Define
Before any prompt or line of code, we write down what the system actually needs to do, for whom, and how you'll know it's working.
Build with AI
We implement against that spec using AI — reviewed, tested and iterated like production code, not accepted on the first output.
Evaluate
We build a lightweight eval set from real inputs so every future change can be measured, not guessed at.
Hand over
You get the spec, the code or prompts, and the evals — no black box, no lock-in.
Got an AI feature that looks done but isn't?
Tell us what it's supposed to do and where it's falling short of production — we'll tell you honestly whether we can help.