DataRoot Labs vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
DataRoot Labs (4.6/5) edges ahead of EPAM Systems (3.9/5) 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.. EPAM Systems is the stronger option for very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform.. The right choice depends on your project size, budget, and required tech stack.
DataRoot Labs vs EPAM Systems: head-to-head summary
| Criterion | DataRoot Labs | EPAM Systems |
|---|---|---|
| Founded | 2016 | 1993 |
| HQ | Kyiv, Ukraine | Newtown, USA |
| Team size | 51–200 | 10,000+ |
| Rating | 4.6 / 5 | 3.9 / 5 |
| Best for | Startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects. | Very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform. |
| Pricing model | Time & Material, project-based | Not published; enterprise project engagements |
| Min. engagement | $10,000+ | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | AWS SageMaker, Amazon Bedrock, EPAM DIAL (proprietary) |
| Industries served | E-commerce, Healthcare, Enterprise software, Robotics | Financial services, Life sciences, Media, Travel and hospitality |
DataRoot Labs vs EPAM Systems: 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.
EPAM Systems
EPAM Systems was founded in 1993 in Newtown, Pennsylvania by Arkadiy Dobkin and Leo Lozner, and has grown into a publicly traded (NYSE: EPAM) global engineering company with more than 53,000 employees. EPAM's AI/ML practice includes model development and deployment on Amazon SageMaker and Amazon Bedrock, MLOps, and its proprietary DIAL platform, an enterprise AI orchestration layer. The company was named AWS Global Innovation Partner of the Year in 2025 and holds AWS Premier Tier Services Partner status, reflecting deep hyperscaler-certified delivery capability at very large scale.
Services and capabilities: DataRoot Labs vs EPAM Systems
| Capability | DataRoot Labs | EPAM Systems |
|---|---|---|
| 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 EPAM Systems
| Framework / platform | DataRoot Labs | EPAM Systems |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | ✓ |
| Amazon Bedrock | 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 EPAM Systems
| Criterion | DataRoot Labs | EPAM Systems |
|---|---|---|
| Minimum engagement | $10,000+ | Not published |
| Engagement models | Time & Material, Fixed project, Dedicated team | Enterprise project engagement, Managed AI services |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: DataRoot Labs vs EPAM Systems
| Dimension | DataRoot Labs | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | E-commerce, Healthcare, Enterprise software | Financial services, Life sciences, Media |
| 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 | Very large enterprises needing an AWS Global Partner of the Year-caliber vendor for ML platform work, Deploying models on Amazon SageMaker or Bedrock with EPAM's proprietary DIAL orchestration layer |
| Typical project type | Time & Material | Enterprise project engagement |
DataRoot Labs vs EPAM Systems: 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. |
| EPAM Systems | |
|---|---|
| + | 2025 AWS Global Innovation Partner of the Year, an independently awarded distinction from AWS itself. |
| + | Proprietary DIAL orchestration platform provides a differentiated technical asset beyond standard consulting delivery. |
| + | Publicly traded (NYSE: EPAM) with substantial financial transparency and scale (53,000+ employees). |
| + | AWS Premier Tier Services Partner status confirms deep, audited hyperscaler certification. |
| - | Very large, generalist software engineering brand means ML/AI is one of many practice areas, not a dedicated specialization. |
| - | No clearly located aggregate Clutch/G2 star rating specific to its AI practice in available public sources. |
| - | Pricing model and minimum engagement are not published, and enterprise minimums are typically substantial. |
| - | Named client-specific ML case studies were not clearly surfaced in available search results. |
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 EPAM Systems?
EPAM Systems is the right choice for very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform..
Proprietary EPAM DIAL platform for enterprise AI orchestration, combined with the 2025 AWS Global Innovation Partner of the Year distinction, an award-level differentiator not held by most peers.. Minimum engagement starts at Not published. Works best with clients in Financial services, Life sciences, Media, Travel and hospitality.
Decision matrix: DataRoot Labs vs EPAM Systems
| 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 EPAM Systems (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 EPAM Systems
| Use case | DataRoot Labs fit | EPAM Systems 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 | Limited | DataRoot Labs |
| Very large enterprises needing an AWS Global Partner of the Year-caliber vendor for ML platform work | Limited | Strong | EPAM Systems |
| Deploying models on Amazon SageMaker or Bedrock with EPAM's proprietary DIAL orchestration layer | Limited | Strong | EPAM Systems |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Limited | Strong | EPAM Systems |
Verdict: DataRoot Labs vs EPAM Systems
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..
EPAM Systems (3.9/5) is the better choice when very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform.. If your situation matches those criteria, EPAM Systems is a competitive option.
Related comparisons
DataRoot Labs vs EPAM Systems FAQ
Is DataRoot Labs better than EPAM Systems?
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.. EPAM Systems is better for very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform..
How do DataRoot Labs and EPAM Systems differ in pricing?
DataRoot Labs uses time & material, project-based pricing with a minimum engagement of $10,000+. EPAM Systems uses not published; enterprise project engagements 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 EPAM Systems?
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 company before shortlisting.
What are the main differences between DataRoot Labs and EPAM Systems?
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).. EPAM Systems's primary differentiator is: proprietary epam dial platform for enterprise ai orchestration, combined with the 2025 aws global innovation partner of the year distinction, an award-level differentiator not held by most peers.. They also differ in team size (51–200 vs 10,000+), minimum engagement ($10,000+ vs Not published), and primary industries served (E-commerce, Healthcare vs Financial services, Life sciences).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.