About Datapoch

An engineering studio, not an agency with a sales layer

We started Datapoch because most "AI agencies" were selling slide decks, not systems. We wanted to build the thing itself — and stay accountable to whether it actually works in production.

Our story

From notebooks to production systems

Datapoch was founded by a small group of engineers who kept running into the same problem on client work: the model that performed well in a notebook rarely survived contact with real traffic, real edge cases, and real users. Most of the hard work in AI isn't training the model — it's everything around it: the data pipeline, the monitoring, the fallback behavior when the model is wrong.

So we built a studio around that gap. Every engagement is scoped and delivered by the same engineers, end to end — no handoff between the person who sold the project and the person who has to make it work. We work across the full stack, because an AI feature is only as good as the product it's embedded in.

Today we work with startups shipping their first AI feature and established companies modernizing systems that have run the same way for a decade. The through-line is the same either way: build something that keeps working after we leave.

What we believe

Values that shape how we work

// 01

Ship, don't demo

A model that works once in a meeting isn't done. We measure success in production, not in a pitch.

// 02

Own the whole stack

Data, model, backend, frontend — one team accountable for all of it, not a chain of handoffs.

// 03

No lock-in by design

We build on open, current tools your own team can maintain — not proprietary black boxes.

// 04

Say the quiet part

If something won't work, we say so before you pay for it, not after.

The team

Engineers you'll actually talk to

Small, senior, and hands-on — the people scoping your project are the ones building it.

AN

A. Novak

Founder / Lead ML Engineer

8 years building production ML systems, from recommendation engines to LLM agents.

PT

P. Thakur

Lead Backend Engineer

Focused on data infrastructure and APIs that hold up under real production load.

EL

E. Laurent

Lead Frontend Engineer

Builds the interfaces that make AI features feel like a natural part of the product.

MO

M. Owusu

Mobile Engineer

Ships cross-platform and native apps with on-device and API-backed AI features.

RH

R. Haddad

MLOps & Infrastructure

Keeps models monitored, versioned, and reliable once they're live.

SC

S. Choi

Project & Delivery Lead

Keeps scoping honest and checkpoints weekly, so nothing surprises you at handover.

Want to work with this team?

Tell us what you're building — we'll reply within one business day.