Top AI Development Agencies

DataRoot Labs vs HYS Enterprise: full comparison for 2026

Quick verdict

DataRoot Labs (4.4/5) edges ahead of HYS Enterprise (3.9/5) overall. DataRoot Labs is the better choice for startups needing applied ML research capacity. HYS Enterprise is the stronger option for EU clients wanting Netherlands-based contracting with Poland delivery. The right choice depends on your project size, budget, and required tech stack.

DataRoot Labs vs HYS Enterprise: head-to-head summary

Criterion DataRoot Labs HYS Enterprise
Founded 2016 2007
HQ Kyiv, Ukraine Amsterdam, Netherlands
Team size 11-50 213
Rating 4.4 / 5 3.9 / 5
Primary differentiator Research-oriented engagement style built for startup speed, not enterprise procurement Amsterdam legal entity with an Eastern European delivery hub for EU-based contracting
Pricing model Dedicated team or fixed project Fixed project or dedicated team
Min. engagement Not disclosed Not disclosed
Primary tech stack Python, PyTorch, scikit-learn Python, AWS, Azure
Industries served Healthtech, Fintech, Retail & e-commerce Fintech, Healthcare, Retail & e-commerce

DataRoot Labs vs HYS Enterprise: overview

DataRoot Labs

DataRoot Labs runs out of Kyiv and has focused on applied data science research since founding in 2016. Public staff counts vary widely, from about 11 to nearly 200 depending on the source, likely a function of how contractors get counted differently across trackers. What's consistent is the specialty: machine learning models, computer vision pipelines, and hands-on AI R&D for startups that need research capability without hiring a full internal team.

HYS Enterprise

HYS Enterprise was founded in 2007 and is headquartered in Amsterdam, with its main development hub staffed by engineers across Eastern Europe based in Poland. As of mid-2026 the company reported 213 employees. It operates as an IT consulting and software development agency broadly, with AI delivered as an extension of its general consulting and engineering practice rather than a dedicated specialty area.

Services and capabilities: DataRoot Labs vs HYS Enterprise

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

Tech stack comparison: DataRoot Labs vs HYS Enterprise

Framework / platform DataRoot Labs HYS Enterprise
Python
PyTorch N/A
TensorFlow N/A N/A
LangChain N/A N/A
AWS
Azure N/A
Kubernetes N/A N/A

Pricing comparison: DataRoot Labs vs HYS Enterprise

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

Target audience comparison: DataRoot Labs vs HYS Enterprise

Dimension DataRoot Labs HYS Enterprise
Best company size Startup to mid-market Startup to mid-market
Best industries Healthtech, Fintech, Retail & e-commerce Fintech, Healthcare, Retail & e-commerce
Best use cases Standing up an ML proof of concept ahead of a seed round., Getting a second, independent build on a computer vision pipeline. Getting EU-based contracting terms with Eastern European delivery costs., Running a general IT consulting engagement that includes an AI component.
Typical project type Dedicated team Fixed project

DataRoot Labs vs HYS Enterprise: pros and cons

DataRoot Labs
+ Research culture suits startups needing genuine experimentation over templated builds.
+ Small team keeps direct communication between founders and the engineers doing the work.
+ Kyiv talent pool offers strong ML fundamentals at lower cost than US or Western European teams.
+ Named computer vision projects back up the firm's stated specialty.
- Employee counts differ substantially across public sources, making capacity hard to verify
- Little public evidence of enterprise-scale delivery experience
HYS Enterprise
+ Amsterdam headquarters simplifies EU-based contracting and data residency conversations.
+ Eastern European delivery hub keeps costs lower than a fully Western European team.
+ Nearly two decades of IT consulting experience.
+ Consistent, precisely reported headcount (213) rather than a wide estimated range.
- AI is delivered as an extension of general IT consulting rather than a dedicated practice
- Smaller team than most enterprise-scale agencies on this list, limiting very large program capacity

Who should choose DataRoot Labs?

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

Research-oriented engagement style built for startup speed, not enterprise procurement. Minimum engagement is not publicly disclosed. Works best with clients in Healthtech, Fintech, Retail & e-commerce.

Who should choose HYS Enterprise?

A typical fit: getting EU-based contracting terms with Eastern European delivery costs.

Amsterdam legal entity with an Eastern European delivery hub for EU-based contracting. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Healthcare, Retail & e-commerce.

Decision matrix: DataRoot Labs vs HYS Enterprise

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 HYS Enterprise (Not disclosed)
You need specialist depth in a specific vertical DataRoot Labs
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 HYS Enterprise

Use case DataRoot Labs fit HYS Enterprise fit Winner
Standing up an ML proof of concept ahead of a seed round. Strong Limited DataRoot Labs
Getting a second, independent build on a computer vision pipeline. Strong Strong Both equally
Getting EU-based contracting terms with Eastern European delivery costs. Strong Strong Both equally
Running a general IT consulting engagement that includes an AI component. Limited Strong HYS Enterprise
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: DataRoot Labs vs HYS Enterprise

DataRoot Labs (4.4/5) is the stronger overall choice for most AI Development projects. Research-oriented engagement style built for startup speed, not enterprise procurement.

HYS Enterprise (3.9/5) is worth a look if you need running a general IT consulting engagement that includes an AI component. If your situation matches that, HYS Enterprise is a competitive option.

Related comparisons

DataRoot Labs vs HYS Enterprise FAQ

Is DataRoot Labs better than HYS Enterprise?

DataRoot Labs (4.4/5) 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. HYS Enterprise's strongest advantage: amsterdam headquarters simplifies EU-based contracting and data residency conversations.

How do DataRoot Labs and HYS Enterprise differ in pricing?

DataRoot Labs uses dedicated team or fixed project pricing. HYS Enterprise uses fixed project or dedicated team 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 HYS Enterprise?

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

What are the main differences between DataRoot Labs and HYS Enterprise?

DataRoot Labs's primary differentiator is: research-oriented engagement style built for startup speed, not enterprise procurement. HYS Enterprise's primary differentiator is: amsterdam legal entity with an Eastern European delivery hub for EU-based contracting. They also differ in team size (11-50 vs 213), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthtech, Fintech vs Fintech, Healthcare).

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