EPAM Systems vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
DataArt (3.9/5) edges ahead of EPAM Systems (3.8/5) overall. DataArt is the better choice for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. EPAM Systems is the stronger option for the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner.. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs DataArt: head-to-head summary
| Criterion | EPAM Systems | DataArt |
|---|---|---|
| Founded | 1993 | 1997 |
| HQ | Newtown, Pennsylvania, USA | New York, USA |
| Team size | 10,000+ | 5,001–10,000 |
| Rating | 3.8 / 5 | 3.9 / 5 |
| Best for | The largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner. | Enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner. |
| Pricing model | Managed services and fixed project | Fixed project, dedicated team, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, EPAM DIAL, Azure OpenAI | Python, Azure OpenAI, AWS |
| Industries served | Financial Services, Healthcare, Retail, Technology/SaaS, Government | Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality |
EPAM Systems vs DataArt: overview
EPAM Systems
EPAM Systems is a global digital engineering company founded in 1993 by Arkadiy Dobkin and Leo Lozner, listed on the NYSE since 2012, with approximately 62,850 employees as of end of 2025. The company has built a proprietary AI orchestration platform, EPAM DIAL, for managing large language models in production, but AI/ML delivery represents one part of an enormous, broadly diversified enterprise engineering portfolio.
DataArt
DataArt is a software engineering and consulting company founded in 1997 in New York by Eugene Goland, with roughly 5,400 employees across more than 30 locations spanning the US, Europe, Latin America, India, and the UAE. The firm added an Advanced AI Strategy Consulting service line in 2024, delivering data, analytics, and AI/ML work alongside its long-standing core software engineering practice.
Services and capabilities: EPAM Systems vs DataArt
| Capability | EPAM Systems | DataArt |
|---|---|---|
| Custom ML model development | ✓ | ✓ |
| Deep learning & computer vision | ✗ | ✗ |
| NLP & LLM / Generative AI | ✓ | ✗ |
| MLOps & production deployment | ✓ | ✗ |
| Data engineering | ✗ | ✓ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✓ | ✓ |
Tech stack comparison: EPAM Systems vs DataArt
| Framework / platform | EPAM Systems | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | ✓ | N/A |
| Databricks | N/A | ✓ |
| LangChain | N/A | N/A |
Pricing comparison: EPAM Systems vs DataArt
| Criterion | EPAM Systems | DataArt |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Managed services, Fixed project, Staff augmentation | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / not published | Enterprise / not published |
Target audience comparison: EPAM Systems vs DataArt
| Dimension | EPAM Systems | DataArt |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Financial Services, Healthcare, Retail | Financial Services, Media & Entertainment, Healthcare |
| Best use cases | Global enterprises needing AI delivered at a scale only a 60,000+ employee firm can support, Programs that specifically want to leverage the EPAM DIAL LLM orchestration platform | Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery, Media or travel companies needing broad-based data and AI/ML capability |
| Typical project type | Managed services | Fixed project |
EPAM Systems vs DataArt: pros and cons
| EPAM Systems | |
|---|---|
| + | Largest, most globally distributed team on this list, supporting essentially unlimited program scale |
| + | NYSE listing (since 2012) provides the highest level of public financial transparency among firms reviewed here |
| + | Proprietary EPAM DIAL platform for LLM orchestration shows real internal AI infrastructure investment |
| + | 32 years of continuous operation across more than 55 countries |
| - | AI/ML is a specialization within an enormous generalist engineering portfolio, not the company's defining focus |
| - | Scale of the organization can translate into higher account-management overhead for smaller engagements |
| - | Buyers wanting a boutique, founder-accessible relationship will find that better served by smaller firms on this list |
| DataArt | |
|---|---|
| + | 28 years of continuous operation under the same founder-led leadership |
| + | 30+ global delivery locations across five regions supports broad geographic coverage |
| + | Named AI Strategy Consulting service line launched in 2024 shows deliberate recent AI investment |
| + | Broad industry coverage spanning finance, media, healthcare, and travel |
| - | AI Strategy Consulting is a comparatively recent addition (2024) versus firms with a decade-plus dedicated AI/ML focus |
| - | 5,400-employee scale sits within a broad general software-engineering practice rather than an AI-first firm |
| - | Minimum engagement size not publicly disclosed |
Who should choose EPAM Systems?
EPAM Systems is the right choice for the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner..
Largest headcount on this list (62,000+) with NYSE-listed financial transparency and a proprietary LLM orchestration platform (EPAM DIAL).. Minimum engagement starts at Not published. Works best with clients in Financial Services, Healthcare, Retail, Technology/SaaS, Government.
Who should choose DataArt?
DataArt is the right choice for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated AI strategy consulting service line.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality.
Decision matrix: EPAM Systems vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | EPAM Systems |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Compare: EPAM Systems (Not published) vs DataArt (Not published) |
| You need specialist depth in a specific vertical | EPAM Systems |
| You need staff augmentation or team extension | EPAM Systems |
| You need consulting before committing to a build | EPAM Systems |
Use case fit: EPAM Systems vs DataArt
| Use case | EPAM Systems fit | DataArt fit | Winner |
|---|---|---|---|
| Global enterprises needing AI delivered at a scale only a 60,000+ employee firm can support | Strong | Strong | Both equally |
| Programs that specifically want to leverage the EPAM DIAL LLM orchestration platform | Strong | Strong | Both equally |
| Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery | Strong | Strong | Both equally |
| Media or travel companies needing broad-based data and AI/ML capability | Limited | Strong | DataArt |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: EPAM Systems vs DataArt
DataArt (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated AI strategy consulting service line.. It is best for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
EPAM Systems (3.8/5) is the better choice when the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner.. If your situation matches those criteria, EPAM Systems is a competitive option.
Related comparisons
EPAM Systems vs DataArt FAQ
Is EPAM Systems better than DataArt?
DataArt (3.9/5) scores higher overall, but "better" depends on your use case. EPAM Systems is better for the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner.. DataArt is better for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
How do EPAM Systems and DataArt differ in pricing?
EPAM Systems uses managed services and fixed project pricing with a minimum engagement of Not published. DataArt uses fixed project, dedicated team, staff augmentation 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: EPAM Systems or DataArt?
DataArt 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 EPAM Systems and DataArt?
EPAM Systems's primary differentiator is: largest headcount on this list (62,000+) with nyse-listed financial transparency and a proprietary llm orchestration platform (epam dial).. DataArt's primary differentiator is: 28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated ai strategy consulting service line.. They also differ in team size (10,000+ vs 5,001–10,000), minimum engagement (Not published vs Not published), and primary industries served (Financial Services, Healthcare vs Financial Services, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.