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Zeropoint Studio

Germany · remote across DACH, US & UK

Web apps and AI features, built end to end — functional and great to use.

I design and ship complete web applications end to end — from the core logic to a genuinely great interface, all the way to production. AI and LLMs are a specialty, brought in when they add real value. One person who owns it all, and measures quality along the way.

The problem

The gap between “demo” and “product”

AI ships faster than teams can turn it into something real. A demo impresses; a product has to be reliable, usable, and trustworthy in the messy real world — the confident-but-wrong answer handled gracefully, the long wait made bearable, the error caught before a user sees it. Closing that gap is the whole job — and measuring quality as I go is how I keep it closed.

Proof

Systems in production, not slideware

Two projects that show the loop end to end — measured quality and the interface around it.

What I do

One person for the whole build

Most AI consultants deliver a backend script; most agencies deliver a UI with no substance behind it. I build the entire feature — the AI, the interface, and the production plumbing — done well.

01

End-to-end implementation

The whole application, not a notebook — data model, API, UI, and deployment, with an AI/LLM core when the product calls for it. One person owns it end to end, from first prototype to running in production, so nothing falls between specialists.

02

Excellent usability & UI

Four years of React/TypeScript craft most AI engineers don't have. Interfaces that make AI genuinely usable: clear flows, perceived-performance for slow model calls, graceful handling of uncertainty — the layer where users decide whether to trust it.

03

AI / LLM engineering

The AI done right: RAG (hybrid retrieval, reranking), agents and tool use, prompt and context engineering, streaming. Real integration of the Claude API and modern LLM tooling — not a thin wrapper.

How it works

A calm, low-risk way to start

  1. 01

    Discovery

    An honest call. We figure out what's at stake and where the real risk is. No forms, no jargon.

  2. 02

    A scoped first step

    Usually an eval-system concept on your real data: baseline metrics and an error analysis, so we both know exactly where you stand.

  3. 03

    Build & measure

    I build the feature end to end — the eval loop and the interface people actually use — and every change is measured, not guessed.

  4. 04

    Keep it improving

    A system that gets better with use instead of quietly rotting. Optional ongoing eval maintenance keeps quality from drifting.

Engagements

Clear ways to work together

End-to-End Build

Most popular

Your product, built and shipped end to end — web app or AI feature. From the core logic and API to a polished interface and production. One person, the whole thing.

from €15,000

AI Feature Build

A focused build: turn a specific idea — a RAG assistant, an agent, a chat feature — into a working, well-designed product. Great for a first project together.

project-based

Frontend / Full-Stack

Need senior React/TypeScript or full-stack hands? Day-rate work — AI feature or not.

day rate on request

Ongoing development

Keep building after launch: new features, iteration, and quality kept measured as your product grows.

monthly retainer

Indicative starting points — final scope and price are set together.

The plus most builders skip: I measure quality as I build — baseline metrics, error analysis, LLM-as-judge — so “it works” isn't a guess. That's how end-to-end delivery stays trustworthy.
Quality, measured

About

Product-minded developer who builds the whole thing — web apps and AI features that reach production.

HP

I'm Hac Hai. I build complete web applications end to end — the interface, the backend, the API, and the path to production — as one person who owns the whole thing. AI and LLMs are my specialty, brought in when they genuinely add value; plenty of what I build has no AI at all — a solid web app is a solid web app.

Most AI consultants hand over a backend script, and most agencies hand over a UI with nothing behind it. I do both — and I measure quality as I build (baseline metrics, error analysis, LLM-as-judge), so “it works” isn't a guess and it can face real customers.

Background: four years building production React/TypeScript in a large Nx monorepo — component libraries, E2E testing, Auth0/Keycloak — plus deep AI and evaluation work: an open-source RAG system with a full evaluation framework, and a research platform running in production for an NGO health clinic, which I delivered end to end as lead developer.

I'm product-centered: I lead with the user and the outcome, not just the code, with a strong intuition for how something feels to use. I work best with people who bring deep domain expertise — you bring the domain, together we work out what to build and what success looks like, and I take care of the technical side end to end.

What I work with

Frontend
ReactNext.jsTypeScriptTailwindNxTanStack QueryStorybookPlaywright
AI / LLM
RAG (pgvector + BM25)Eval harnessesLLM-as-judgePydantic-AILangGraphClaude APILangfuse
Backend / Infra
PythonFastAPIPydanticNode.jsPostgreSQLDockerCI/CD
Auth / Security
Auth0Keycloak

FAQ

Questions people ask first

What exactly do you do?
I build web applications end to end — from the interface and backend to deployment — as one person who owns the whole thing. AI and LLMs are a specialty I bring in when the product calls for it: RAG systems, agents, chat and assistant features, and the well-crafted UIs around them.
Do you build the whole thing, or just the AI part?
The whole thing. Most AI consultants deliver a backend script, most agencies deliver a UI with no substance. I do both — interface and backend — plus API, deployment, and running it in production. And plenty of what I build has no AI at all: a solid web app is a solid web app.
What does a first engagement look like?
Usually a focused AI Feature Build: turning a specific idea — a RAG assistant, an agent, a chat feature — into a working, well-designed product. Scoped and low-risk, and we both see how working together goes before anything bigger.
What about evaluation?
Evaluation is my plus, not a separate purchase: I measure quality as I build — baseline metrics, error analysis, LLM-as-judge — so “it works” isn't a guess. That keeps the feature trustworthy in production, without you having to commission a separate eval project.
Who do you work with?
Startups and scale-ups with an AI feature that needs to reach production reliability, and NGOs or teams moving a single AI feature from demo to production. Remote across DACH (Germany, Austria, Switzerland) plus the US and UK.
What's your stack?
Frontend: React, Next.js, TypeScript, Tailwind. AI/LLM: RAG (pgvector + BM25), agents, Pydantic-AI, LangGraph, the Vercel AI SDK, the Claude API, Langfuse, LLM-as-judge. Backend: Python, FastAPI, PostgreSQL, Docker.
How much does it cost?
End-to-end builds — web app or AI feature — start around €15,000; focused feature builds are priced project-based, and frontend/full-stack work runs at a day rate. Every engagement is priced to the value at stake — let's talk about what you need.

Local

Based in Bad Lippspringe, Germany

I'm based in Bad Lippspringe, North Rhine-Westphalia — local enough to meet in person around the region, and set up to work remotely with teams across Germany, the wider DACH area, the US, and the UK.

51.783° N · 8.817° E

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Contact

Have a process or product that should exist as software?

If you bring the domain expertise — or you're a seed / Series A team that needs strong hands — I'll handle the technical side end to end, or work with your team to ship a product people love to use.