DATANOMIQ — DATA · AI · ENGINEERING

About us

An independent partner for data, AI & software.

The DATANOMIQ team — seven colleagues standing together outdoors in Berlin.
Five DATANOMIQ colleagues at a technology conference, in front of an event backdrop.
DATANOMIQ team sharing a meal together at a restaurant.
DATANOMIQ speakers on stage at an event, presenting in front of a slide on AI.
Two DATANOMIQ colleagues at an outdoor event beside a DATANOMIQ banner.
01Founded 2015 in Berlin
02500+ successful data & software projects
03Full end-to-end delivery — data, AI, and production software
0450+ customers across healthcare, e-commerce, automotive, and more
Method
The MethodHow we prioritize

Value Engineering.

A structured way to drive measurable value from data, AI & software — instead of slideware.

What is Value Engineering?

A structured, data-driven way to maximize program value.

At DATANOMIQ, Value Engineering is a structured, data-driven way to maximize the value of a program: strengthen what matters for outcomes, control cost and risk, and protect quality — without boiling the ocean.

In short: Value Engineering keeps AI, data, and software work anchored to real, measurable business value — not slideware.

Why it matters for AI, data & software

Most AI and data programs still stall in pilot purgatory — and software spend rises fast when use cases are fuzzy. They break through when teams map initiatives to measurable impact from day one: cost, efficiency, revenue, risk, or reliability.

  1. i.Clear mapping from use cases to business value (savings, speed, revenue, risk reduction).
  2. ii.Focus on high-ROI opportunities before large platform bets.
  3. iii.Early feasibility checks so you do not sink cost into the wrong problem.
  4. iv.Fast validation cycles — MVPs and minimum viable data products — aligned with a “fail fast, learn fast” culture.

How we apply it

Three steps. Repeated, never skipped.

Step 01 · Score

We use a 2×2 Value Matrix to score opportunities systematically — impact vs. effort — so prioritization is explicit, not political.

Step 02 · Ship

We ship in weeks, not years: thin slices, real users, real metrics — then iterate. The same mindset applies to data platforms, models, and production software.

Step 03 · Scale

We only scale what works. Double down on proven value; pause or redesign what does not clear the bar.

Fig. 01 · The 2×2 Value Matrix

Beyond data

Beyond data

We are not only a data house — we ship production software too.

DATANOMIQ helps organizations unlock measurable business value by combining data platforms, analytics, machine learning, and engineering that runs in the real world: APIs, applications, integrations, and reliable operations alongside your teams.

Driven by curiosity, pragmatism, and a strong “let’s do it” mentality, we work side by side with clients from strategy to production — turning complexity into clarity and ideas into impact.

NEXT STEP

Ready to move faster? Let’s build it together.

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