Best AI Development Services Europe

DataRoot Labs vs ITRex Group: full comparison for 2026

Quick verdict

DataRoot Labs (4.3/5) edges ahead of ITRex Group (3.9/5) overall. DataRoot Labs is the better choice for european startups needing applied AI research on European time zones. ITRex Group is the stronger option for US-based enterprises open to a non-EU AI vendor. The right choice depends on your project size, budget, and required tech stack.

DataRoot Labs vs ITRex Group: head-to-head summary

Criterion DataRoot Labs ITRex Group
Founded 2016 2009
HQ Kyiv, Ukraine Santa Monica, United States
Team size 11-50 201-250
Rating 4.3 / 5 3.9 / 5
Primary differentiator Research-oriented engagement style in an EU-adjacent time zone for European founders Fifteen-plus years combining AI delivery with data engineering, based in the US
Pricing model Dedicated team or fixed project Fixed project, dedicated team, or retainer
Min. engagement Not disclosed Not disclosed
Primary tech stack Python, PyTorch, scikit-learn Python, TensorFlow, AWS
Industries served Healthtech, Fintech, Retail & e-commerce Healthcare, Manufacturing, Retail & e-commerce, Logistics

DataRoot Labs vs ITRex Group: overview

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.

ITRex Group

ITRex has been based in Southern California since 2009, with public headcount estimates ranging from around 221 up to over 250 employees across three continents. The agency pairs AI and machine learning with data analytics and cloud computing, though its published delivery footprint centers on North America rather than Europe, which European buyers should factor into any data-residency planning.

Services and capabilities: DataRoot Labs vs ITRex Group

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

Tech stack comparison: DataRoot Labs vs ITRex Group

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

Pricing comparison: DataRoot Labs vs ITRex Group

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

Target audience comparison: DataRoot Labs vs ITRex Group

Dimension DataRoot Labs ITRex Group
Best company size Startup to mid-market Startup to mid-market
Best industries Healthtech, Fintech, Retail & e-commerce Healthcare, Manufacturing, Retail & e-commerce
Best use cases 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. Modernizing a legacy data warehouse so it can actually feed an AI model, for a US-based buyer., Running an AI pilot that needs to connect into existing enterprise cloud systems outside the EU.
Typical project type Dedicated team Fixed project

DataRoot Labs vs ITRex Group: pros and cons

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
ITRex Group
+ Combines AI work with the data engineering most AI projects actually need first.
+ Fifteen-plus years of history across three continents.
+ Enterprise client mix means the team is comfortable with procurement cycles.
+ Works across both AWS and Azure, reducing platform lock-in for clients.
- No reported EU delivery presence, which European clients with data-residency needs should factor in
- Employee counts vary meaningfully across public sources

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.

Who should choose ITRex Group?

A typical fit: modernizing a legacy data warehouse so it can actually feed an AI model, for a US-based buyer.

Fifteen-plus years combining AI delivery with data engineering, based in the US. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Manufacturing, Retail & e-commerce, Logistics.

Decision matrix: DataRoot Labs vs ITRex Group

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

Use case fit: DataRoot Labs vs ITRex Group

Use case DataRoot Labs fit ITRex Group fit Winner
Standing up an ML proof of concept ahead of a European seed round. Strong Limited DataRoot Labs
Getting a second, independent build on a computer vision pipeline from a nearby time zone. Strong Strong Both equally
Modernizing a legacy data warehouse so it can actually feed an AI model, for a US-based buyer. Limited Strong ITRex Group
Running an AI pilot that needs to connect into existing enterprise cloud systems outside the EU. Limited Strong ITRex Group
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: DataRoot Labs vs ITRex Group

DataRoot Labs (4.3/5) is the stronger overall choice for most AI Development projects. Research-oriented engagement style in an EU-adjacent time zone for European founders.

ITRex Group (3.9/5) is worth a look if you need running an AI pilot that needs to connect into existing enterprise cloud systems outside the EU. If your situation matches that, ITRex Group is a competitive option.

Related comparisons

DataRoot Labs vs ITRex Group FAQ

Is DataRoot Labs better than ITRex Group?

DataRoot Labs (4.3/5) scores higher overall, but "better" depends on your use case. DataRoot Labs's strongest advantage: research culture suits startups needing genuine experimentation over templated builds. ITRex Group's strongest advantage: combines AI work with the data engineering most AI projects actually need first.

How do DataRoot Labs and ITRex Group differ in pricing?

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

Which is better for enterprise: DataRoot Labs or ITRex Group?

ITRex Group 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 DataRoot Labs and ITRex Group?

DataRoot Labs's primary differentiator is: research-oriented engagement style in an EU-adjacent time zone for European founders. ITRex Group's primary differentiator is: fifteen-plus years combining AI delivery with data engineering, based in the US. They also differ in team size (11-50 vs 201-250), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthtech, Fintech vs Healthcare, Manufacturing).

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