AI Integration
We add AI where it saves time, like Readme Studio does for documentation.
AI bolted on as a chat box rarely fits the task. Good integration needs structure and clear limits.
What clients bring us, and what we do about it.
- Problem
Writing the same documents takes hours.
SolutionStructured AI generation with an editor, so people review instead of write.
- Problem
AI output is unpredictable.
SolutionConstrained prompts, structured output and a human edit step before anything is published.
Proof from products we built and run.
These are our own live products. Each one uses the same skills this service delivers.
Readme Studio
- Challenge
- A README is the front door of a project, and it is usually written last and in a hurry. Missing setup steps and unclear structure cost every future contributor time.
- What we built
- Readme Studio uses AI to write meaningful, professional README files tailored to your project. Generate a draft, refine it in the built-in markdown editor with a live GitHub-style preview, or start from a pre-built template. It is open source, with more than 100 stars on GitHub.
- AI feature in production
- Prompt library
- Usage monitoring
How the project runs
Discover
A short call and a written brief we both agree on.
Design
Flows and interfaces, reviewed as a clickable prototype.
Build
Typed, tested code with a live preview link from week one.
Launch
Deployment, handover docs and a support window.
Built with our own tools.
We use the open-source tools we make on client work. They are tested in public, and they save you time.
In every project, whatever the size.
- You own everythingCode, designs and documentation are yours at handover.
- Accessible by defaultContrast, keyboard paths, labels and focus states built in.
- Responsive, not squeezedMobile layouts designed as their own compositions.
- Measured performanceSpeed checked before launch, not promised after.
- A live preview linkFollow progress on a working build from week one.
- Written handoverHow it works, how to change it, and what to watch.
Questions
What clients usually ask before a ai integration project. Anything else, ask us directly.
Still deciding?
Tell us what you are planning. We reply with honest options, including when a smaller scope is enough.
Ask about your projectWe choose the model per task, balancing quality, speed and cost, and keep the choice swappable so you are not locked to one provider.
Structured prompts, constrained output formats and a human edit step before anything is published, the same pattern Readme Studio uses.
Only what a feature needs, only to the provider you approve, and never used to train models where the provider offers that option. We document every data flow.
Yes. We audit what you have first and keep whatever is worth keeping.
You do. Everything is handed over at the end of the project.
One shared channel, a written weekly update and a live preview link you can check any time.
Listed prices are starting points. We confirm a fixed quote after a short discovery call.