Best ML Model Development Companies

DataRoot Labs vs ELEKS: full comparison for 2026

Last updated: July 2026

Quick verdict

DataRoot Labs (4.6/5) edges ahead of ELEKS (4.1/5) overall. DataRoot Labs is the better choice for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects.. ELEKS is the stronger option for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.. The right choice depends on your project size, budget, and required tech stack.

DataRoot Labs vs ELEKS: head-to-head summary

Criterion DataRoot Labs ELEKS
Founded 2016 1991
HQ Kyiv, Ukraine Tallinn, Estonia (engineering hub: Lviv, Ukraine)
Team size 51–200 1,001–5,000
Rating 4.6 / 5 4.1 / 5
Best for Startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects. Enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.
Pricing model Time & Material, project-based Time & Material, Fixed project
Min. engagement $10,000+ Not published
Primary tech stack Python, PyTorch, TensorFlow Python, Cloud ML platforms (AWS/Azure/GCP), Data engineering tooling
Industries served E-commerce, Healthcare, Enterprise software, Robotics Financial services, Healthcare, Manufacturing, Insurance

DataRoot Labs vs ELEKS: overview

DataRoot Labs

DataRoot Labs is a Ukraine-founded machine learning consultancy established in 2016 that has remained AI/ML-only since inception, in contrast to firms that added AI as a service line later. The company offers AI consulting, custom model development and training, solution architecture, and deployment/monitoring, with stated specializations in large language model fine-tuning, computer vision, reinforcement learning, and vector databases. Publicly named clients include OLX, IBM, Databand, and Moxie (Embodied). The company also runs DataRoot University, a training program it states has produced over 6,000 machine learning graduates (per company website; independently unverifiable), which functions as a talent pipeline and community credibility signal.

ELEKS

ELEKS is a long-running European software engineering company founded in 1991, with corporate presence in Tallinn, Estonia and its largest engineering hub in Lviv, Ukraine, alongside additional offices across Europe and North America. The company reports more than 2,000 employees and operates a dedicated data science and AI practice layered onto its broader enterprise software engineering services. Its history predates the modern AI/ML consulting wave by roughly three decades, giving it an unusually long operating track record compared to most peers in this list.

Services and capabilities: DataRoot Labs vs ELEKS

Capability DataRoot Labs ELEKS
Custom model training
Fine-tuning & adaptation
MLOps pipeline
Model deployment & serving
Data engineering for ML
ML infrastructure management
Computer vision
NLP & LLM development
Forecasting & time-series modeling
ML strategy consulting

Tech stack comparison: DataRoot Labs vs ELEKS

Framework / platform DataRoot Labs ELEKS
PyTorch N/A
TensorFlow N/A
MLflow N/A N/A
AWS SageMaker N/A N/A
Amazon Bedrock N/A N/A
Google Cloud N/A N/A
Microsoft Azure N/A N/A
Kubernetes
Snowflake N/A N/A
NVIDIA N/A N/A

Pricing comparison: DataRoot Labs vs ELEKS

Criterion DataRoot Labs ELEKS
Minimum engagement $10,000+ Not published
Engagement models Time & Material, Fixed project, Dedicated team Time & Material, Fixed project, Dedicated team
Rate transparency Minimum disclosed Not public
Price tier Accessible Mid-market

Target audience comparison: DataRoot Labs vs ELEKS

Dimension DataRoot Labs ELEKS
Best company size Startup to mid-market Startup to mid-market
Best industries E-commerce, Healthcare, Enterprise software Financial services, Healthcare, Manufacturing
Best use cases Fine-tuning an open-source LLM for a domain-specific internal tool, Building a computer vision model for retail or logistics quality inspection Running an enterprise-scale data science initiative alongside a broader software modernization program, Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components
Typical project type Time & Material Time & Material

DataRoot Labs vs ELEKS: pros and cons

DataRoot Labs
+ Clutch rating of 4.9/5 across 23 verified reviews, among the highest in this comparison set.
+ Named, checkable clients (OLX, IBM, Databand, Moxie) rather than anonymized case studies only.
+ Full IP transfer to clients is cited as standard practice in reviews.
+ AI-only focus since 2016 avoids the generalist dilution seen in broader software houses.
- Small team (51–200) constrains capacity for large, multi-team enterprise rollouts.
- Delivery is concentrated in Ukraine, which some risk-averse enterprise buyers may flag for business-continuity planning.
- Public tech-stack disclosure is limited beyond high-level specialization claims.
- Minimum engagement of $10K+ is accessible, but larger programs will need custom scoping not published on the site.
ELEKS
+ Over three decades of continuous operation, unusually long for this category.
+ Large engineering bench (2,000+ employees) supports substantial delivery capacity.
+ Data science practice is embedded within a mature enterprise software engineering organization.
+ Multi-region European and North American office footprint.
- AI/ML is one practice area within a much broader enterprise software portfolio, not the company's primary specialization.
- Specific, named ML case studies with quantified outcomes are limited in available public sources.
- Pricing minimums are not published.
- Long operating history does not necessarily translate into deep modern ML/LLM specialization relative to newer, AI-first boutiques.

Who should choose DataRoot Labs?

DataRoot Labs is the right choice for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects..

Has never diversified beyond AI/ML services, and backs its delivery bench with an in-house ML training program (DataRoot University).. Minimum engagement starts at $10,000+. Works best with clients in E-commerce, Healthcare, Enterprise software, Robotics.

Who should choose ELEKS?

ELEKS is the right choice for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor..

One of the longest operating histories (since 1991) among firms researched for this list, predating the AI consulting boom by decades.. Minimum engagement starts at Not published. Works best with clients in Financial services, Healthcare, Manufacturing, Insurance.

Decision matrix: DataRoot Labs vs ELEKS

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 ($10,000+) vs ELEKS (Not published)
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 Both may offer discovery engagements

Use case fit: DataRoot Labs vs ELEKS

Use case DataRoot Labs fit ELEKS fit Winner
Fine-tuning an open-source LLM for a domain-specific internal tool Strong Limited DataRoot Labs
Building a computer vision model for retail or logistics quality inspection Strong Strong Both equally
Running an enterprise-scale data science initiative alongside a broader software modernization program Limited Strong ELEKS
Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components Limited Strong ELEKS
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Limited Limited Both equally

Verdict: DataRoot Labs vs ELEKS

DataRoot Labs (4.6/5) is the stronger overall choice for most ML Model Development projects. Has never diversified beyond AI/ML services, and backs its delivery bench with an in-house ML training program (DataRoot University).. It is best for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects..

ELEKS (4.1/5) is the better choice when enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.. If your situation matches those criteria, ELEKS is a competitive option.

Related comparisons

DataRoot Labs vs ELEKS FAQ

Is DataRoot Labs better than ELEKS?

DataRoot Labs (4.6/5) scores higher overall, but "better" depends on your use case. DataRoot Labs is better for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects.. ELEKS is better for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor..

How do DataRoot Labs and ELEKS differ in pricing?

DataRoot Labs uses time & material, project-based pricing with a minimum engagement of $10,000+. ELEKS uses time & material, fixed project pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: DataRoot Labs or ELEKS?

ELEKS 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 ELEKS?

DataRoot Labs's primary differentiator is: has never diversified beyond ai/ml services, and backs its delivery bench with an in-house ml training program (dataroot university).. ELEKS's primary differentiator is: one of the longest operating histories (since 1991) among firms researched for this list, predating the ai consulting boom by decades.. They also differ in team size (51–200 vs 1,001–5,000), minimum engagement ($10,000+ vs Not published), and primary industries served (E-commerce, Healthcare vs Financial services, Healthcare).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.