AI product development
AI products that ship. And keep working after launch.
We build AI features, copilots and GenAI MVPs on a real software foundation. Senior engineers, AI-assisted development and evals from day one, so you reach a working product fast and own every line of code.
Is this for you?
An honest check before we build.
A good fit if…
You have a clear user and a problem to solve.
AI is core to the product, not a gimmick.
You need a working MVP in weeks, not quarters.
You want to own the code and the roadmap.
Probably not for you if…
You need generic software with no AI in it.
Nobody can make product decisions.
You want a demo, not a product.
It has to be perfect before anyone uses it.
The service
MVPs
Features
Copilots
What we build
01
SaaS
AI features in your SaaS
Search, summaries, drafting and insights inside the product your customers use.
02
Startups
GenAI MVPs
A working first version to test with real users and show investors.
03
Copilots
Copilots and assistants
Helpers that sit inside a workflow and know its context.
04
Internal
Internal AI tools
Tools for your team with an LLM at the core, connected to your data.
Use cases
01
Search
Smart search and Q&A
Users ask in plain language and get answers from your product’s data.
02
Content
Generation and drafting
Reports, emails, listings or briefs drafted in the user’s context.
03
Documents
Document workflows
Upload, extract, review and compare, right inside the app.
04
Insights
Analytics and insights
Summaries and next steps from usage, sales or support data.
Quality
Shipped like real software.
Engineering
Senior code review on every change.
Automated tests and CI/CD from the first sprint.
Evals for every AI feature, run before each release.
You own the code, repositories and accounts.
In production
Tracing and observability with Langfuse.
Cost controls: caching, model routing and usage limits.
Security reviews, secrets management and access control.
Guardrails against prompt injection and data leaks.
Engagement
An MVP sprint. Then we iterate.
We agree the scope, the success metrics and a fixed price upfront. The MVP sprint delivers a working product you can put in front of real users. After that, we iterate in short cycles based on what they do, with optional AI Ops care for monitoring, model updates and cost tuning once you’re live.
From idea to working MVP.
Fixed price, agreed upfront.
Tech stack
01
Frontend
Web and mobile
Next.js and React on the web, React Native for iOS and Android.
02
Backend
Backend and data
Python and FastAPI or Node, with Postgres and pgvector.
03
AI
Models and evals
LLM APIs or open-weight models, traced and evaluated with Langfuse.
04
Cloud
Hosting
Vercel, AWS, Azure or Google Cloud, in your own accounts.
Process
A working build every week.
Real users before launch.
Case studies
AI products in production, and what changed.
FAQ
Should we build an MVP or the full product?
Does AI-assisted development affect quality?
Which technologies do you use?
Who owns the code?
How much does it cost?
How long does it take?
Can you work with our in-house team?
What happens after launch?
