Xebia vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
Xebia (4.0/5) edges ahead of EPAM Systems (3.9/5) overall. Xebia is the better choice for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. 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.
Xebia vs EPAM Systems: head-to-head summary
| Criterion | Xebia | EPAM Systems |
|---|---|---|
| Founded | 2001 | 1993 |
| HQ | Amsterdam, Netherlands (US HQ: Atlanta, USA) | Newtown, USA |
| Team size | 5,001–10,000 | 10,000+ |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Best for | Enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery. | Very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform. |
| Pricing model | Not published; enterprise project engagements | Not published; enterprise project engagements |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Cloud ML platforms (AWS/Azure/GCP), MLOps tooling | AWS SageMaker, Amazon Bedrock, EPAM DIAL (proprietary) |
| Industries served | Financial services, Retail, Manufacturing, Public sector | Financial services, Life sciences, Media, Travel and hospitality |
Xebia vs EPAM Systems: overview
Xebia
Xebia was founded in 2001 by Rob Dielemans and Daan Teunissen in the Netherlands and has grown into a global consultancy spanning data and AI, cloud, automation, and software engineering. The Xebia Group reports between 5,000 and 10,000 employees, with corporate headquarters activity in both the Netherlands and Atlanta, Georgia. Its Data & AI Hub practice focuses on turning AI strategy into production-ready solutions, reflecting a repositioning from Xebia's original software craftsmanship and training-company roots toward an AI-first identity.
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: Xebia vs EPAM Systems
| Capability | Xebia | 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: Xebia vs EPAM Systems
| Framework / platform | Xebia | EPAM Systems |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | 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: Xebia vs EPAM Systems
| Criterion | Xebia | EPAM Systems |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Enterprise project engagement, Dedicated team, Training/enablement | Enterprise project engagement, Managed AI services |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Xebia vs EPAM Systems
| Dimension | Xebia | EPAM Systems |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Financial services, Retail, Manufacturing | Financial services, Life sciences, Media |
| Best use cases | Turning an existing AI strategy or pilot into a production-ready, monitored system, Combining technical training/enablement with hands-on AI model development | 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 | Enterprise project engagement | Enterprise project engagement |
Xebia vs EPAM Systems: pros and cons
| Xebia | |
|---|---|
| + | 25-year software engineering and technical training pedigree underpins its AI delivery credibility. |
| + | Large scale (5,000–10,000 employees) supports substantial enterprise program capacity. |
| + | Explicit focus on production-ready AI rather than strategy-only advisory work. |
| + | Dual US/EU headquarters presence supports transatlantic enterprise clients. |
| - | AI-first repositioning is relatively recent, so its dedicated AI/ML track record is shorter than its overall company history suggests. |
| - | No clearly located aggregate Clutch/G2 star rating in available public sources. |
| - | Pricing model and minimum engagement are not published. |
| - | Large, multi-practice organization means AI/ML delivery quality may vary by regional team. |
| 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 Xebia?
Xebia is the right choice for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..
Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone.. Minimum engagement starts at Not published. Works best with clients in Financial services, Retail, Manufacturing, Public sector.
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: Xebia vs EPAM Systems
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | Xebia |
| Your budget is at the lower end | Compare: Xebia (Not published) vs EPAM Systems (Not published) |
| You need specialist depth in a specific vertical | Xebia |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Xebia |
Use case fit: Xebia vs EPAM Systems
| Use case | Xebia fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Turning an existing AI strategy or pilot into a production-ready, monitored system | Strong | Limited | Xebia |
| Combining technical training/enablement with hands-on AI model development | Strong | Limited | Xebia |
| 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: Xebia vs EPAM Systems
Xebia (4.0/5) is the stronger overall choice for most ML Model Development projects. Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone.. It is best for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..
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.
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Xebia vs EPAM Systems FAQ
Is Xebia better than EPAM Systems?
Xebia (4.0/5) scores higher overall, but "better" depends on your use case. Xebia is better for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. 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 Xebia and EPAM Systems differ in pricing?
Xebia uses not published; enterprise project engagements pricing with a minimum engagement of Not published. 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: Xebia or EPAM Systems?
Xebia 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 Xebia and EPAM Systems?
Xebia's primary differentiator is: quarter-century software craftsmanship and technical training heritage now applied specifically to production ai/ml delivery rather than ai strategy alone.. 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 (5,001–10,000 vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Retail vs Financial services, Life sciences).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.