Best AI Development Services Europe

SoftKraft vs DataRoot Labs: full comparison for 2026

Quick verdict

SoftKraft (4.4/5) edges ahead of DataRoot Labs (4.3/5) overall. SoftKraft is the better choice for EU startups on tight budgets needing a fully local AI team. DataRoot Labs is the stronger option for european startups needing applied AI research on European time zones. The right choice depends on your project size, budget, and required tech stack.

SoftKraft vs DataRoot Labs: head-to-head summary

Criterion SoftKraft DataRoot Labs
Founded 2015 2016
HQ Bielsko-Biala, Poland Kyiv, Ukraine
Team size 11-50 11-50
Rating 4.4 / 5 4.3 / 5
Primary differentiator Fully EU-based team pricing accessibly for startup budgets, not enterprise rates Research-oriented engagement style in an EU-adjacent time zone for European founders
Pricing model Fixed project or dedicated team Dedicated team or fixed project
Min. engagement Not disclosed Not disclosed
Primary tech stack Python, PostgreSQL, Apache Airflow Python, PyTorch, scikit-learn
Industries served Fintech, SaaS, Healthtech Healthtech, Fintech, Retail & e-commerce

SoftKraft vs DataRoot Labs: overview

SoftKraft

SoftKraft was founded in 2015 by CEO Marek Petrykowski and CTO Blazej Kosmowski, running a lean 11-50 person team out of Bielsko-Biala, Poland, an EU member state. Around 70% of its clients come from North America despite the delivery team sitting fully within the EU, which gives European clients a genuinely local option most competitors its size don't offer. The firm's positioning centers on data-driven software, AI, and data engineering built specifically for startups and small-to-mid-sized companies, not enterprise accounts.

DataRoot Labs

DataRoot Labs runs out of Kyiv, Ukraine and has focused on applied data science research since founding in 2016. Public staff counts vary widely, from about 11 to nearly 200, likely a function of how contractors get counted differently across trackers. Its work centers on machine learning models, computer vision pipelines, and hands-on AI R&D for startups, including a number of European clients drawn to its proximity and EU-adjacent time zone rather than a fully offshore team on another continent.

Services and capabilities: SoftKraft vs DataRoot Labs

Capability SoftKraft DataRoot Labs
Generative AI
Machine learning
AI agents
MLOps
AI consulting
Fixed-price projects
Dedicated team model

Tech stack comparison: SoftKraft vs DataRoot Labs

Framework / platform SoftKraft DataRoot Labs
Python
AWS
Azure N/A N/A
OpenAI API N/A N/A
TensorFlow N/A N/A
PyTorch N/A
Kubernetes N/A N/A

Pricing comparison: SoftKraft vs DataRoot Labs

Criterion SoftKraft DataRoot Labs
Minimum engagement Not disclosed Not disclosed
Engagement models Fixed project, Dedicated team Dedicated team, Fixed project
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: SoftKraft vs DataRoot Labs

Dimension SoftKraft DataRoot Labs
Best company size Startup to mid-market Startup to mid-market
Best industries Fintech, SaaS, Healthtech Healthtech, Fintech, Retail & e-commerce
Best use cases Building a data-driven MVP for an EU-based pre-seed or seed-stage startup., Getting AI and data engineering handled by one small, fully EU-based team. Standing up an ML proof of concept ahead of a European seed round., Getting a second, independent build on a computer vision pipeline from a nearby time zone.
Typical project type Fixed project Dedicated team

SoftKraft vs DataRoot Labs: pros and cons

SoftKraft
+ Fully EU-based team (Poland) gives European clients local delivery without an offshore layer.
+ Small team size keeps overhead, and likely cost, below mid-size and enterprise vendors.
+ Founder-led leadership stays close to delivery rather than purely sales.
+ Startup and SME focus means scope and pricing fit smaller EU budgets from the outset.
- Team of 11-50 limits capacity to a handful of concurrent projects
- Less public case-study history than firms with a decade-plus track record
DataRoot Labs
+ Research culture suits startups needing genuine experimentation over templated builds.
+ EU-adjacent time zone simplifies daily collaboration for European founders and product teams.
+ Small team keeps direct communication between founders and the engineers doing the work.
+ Named computer vision projects back up the firm's stated specialty.
- Employee counts differ substantially across public sources, making capacity hard to verify
- Ukraine is not an EU member state, which some regulated European clients may need to factor into data residency planning

Who should choose SoftKraft?

A typical fit: building a data-driven MVP for an EU-based pre-seed or seed-stage startup.

Fully EU-based team pricing accessibly for startup budgets, not enterprise rates. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, SaaS, Healthtech.

Who should choose DataRoot Labs?

A typical fit: standing up an ML proof of concept ahead of a European seed round.

Research-oriented engagement style in an EU-adjacent time zone for European founders. Minimum engagement is not publicly disclosed. Works best with clients in Healthtech, Fintech, Retail & e-commerce.

Decision matrix: SoftKraft vs DataRoot Labs

Your situation Recommended choice
You need full-ownership delivery on a defined project scope SoftKraft
You need a large dedicated team for an ongoing programme SoftKraft
Your budget is at the lower end Compare: SoftKraft (Not disclosed) vs DataRoot Labs (Not disclosed)
You need specialist depth in a specific vertical SoftKraft
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build SoftKraft

Use case fit: SoftKraft vs DataRoot Labs

Use case SoftKraft fit DataRoot Labs fit Winner
Building a data-driven MVP for an EU-based pre-seed or seed-stage startup. Strong Limited SoftKraft
Getting AI and data engineering handled by one small, fully EU-based team. Strong Strong Both equally
Standing up an ML proof of concept ahead of a European seed round. Limited Strong DataRoot Labs
Getting a second, independent build on a computer vision pipeline from a nearby time zone. Strong Strong Both equally
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: SoftKraft vs DataRoot Labs

SoftKraft (4.4/5) is the stronger overall choice for most AI Development projects. Fully EU-based team pricing accessibly for startup budgets, not enterprise rates.

DataRoot Labs (4.3/5) is worth a look if you need getting a second, independent build on a computer vision pipeline from a nearby time zone. If your situation matches that, DataRoot Labs is a competitive option.

Related comparisons

SoftKraft vs DataRoot Labs FAQ

Is SoftKraft better than DataRoot Labs?

SoftKraft (4.4/5) scores higher overall, but "better" depends on your use case. SoftKraft's strongest advantage: fully EU-based team (Poland) gives European clients local delivery without an offshore layer. DataRoot Labs's strongest advantage: research culture suits startups needing genuine experimentation over templated builds.

How do SoftKraft and DataRoot Labs differ in pricing?

SoftKraft uses fixed project or dedicated team pricing. DataRoot Labs uses dedicated team or fixed project pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: SoftKraft or DataRoot Labs?

SoftKraft is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.

What are the main differences between SoftKraft and DataRoot Labs?

SoftKraft's primary differentiator is: fully EU-based team pricing accessibly for startup budgets, not enterprise rates. DataRoot Labs's primary differentiator is: research-oriented engagement style in an EU-adjacent time zone for European founders. They also differ in team size (11-50 vs 11-50), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Fintech, SaaS vs Healthtech, Fintech).

Verify all details directly with each company before making a decision.