Oxagile vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
EPAM Systems (3.9/5) edges ahead of Oxagile (3.8/5) overall. EPAM Systems is the better choice for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration. Oxagile is the stronger option for media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise. The right choice depends on your project size, budget, and required tech stack.
Oxagile vs EPAM Systems: head-to-head summary
| Criterion | Oxagile | EPAM Systems |
|---|---|---|
| Founded | 2005 | 1993 |
| HQ | New York, NY, USA | Newtown, PA, USA |
| Team size | 250–500 | 62,000+ |
| Rating | 3.8 / 5 | 3.9 / 5 |
| Best for | Media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise | Large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration |
| Pricing model | Fixed project, T&M, Dedicated team | Dedicated team, T&M, Fixed project, Staff augmentation |
| Min. engagement | $25K | $50K |
| Primary tech stack | TensorFlow, PyTorch, OpenCV | Python, TensorFlow, PyTorch |
| Industries served | media, advertising, retail, sports, healthcare | financial services, healthcare, retail, media, government |
Oxagile vs EPAM Systems: overview
Oxagile
Oxagile is a custom software development vendor founded in 2005 and headquartered in New York, with delivery centers in Eastern Europe. The company has 20+ years of video domain expertise and has applied machine learning to video understanding, visual search, and real-time video analytics for clients in media, advertising, sports, and retail. Oxagile's ML practice is particularly strong in use cases where video processing is the core data source.
EPAM Systems
EPAM Systems is a global technology engineering company founded in 1993 and headquartered in Newtown, Pennsylvania. The company employs 62,000+ engineers across 50+ countries and is publicly traded on the NYSE. EPAM provides end-to-end AI development services from strategy and consulting to implementation and support, working with Fortune 500 clients across financial services, healthcare, retail, media, and government. EPAM is the largest firm in this review, with AI/ML capabilities delivered within a full-service technology engineering operation.
Services and capabilities: Oxagile vs EPAM Systems
| Capability | Oxagile | EPAM Systems |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| ML consulting | ✓ | ✓ |
| Deep learning | ✓ | ✗ |
| NLP | ✗ | ✗ |
| Computer vision | ✓ | ✗ |
| MLOps | ✗ | ✓ |
| Predictive analytics | ✗ | ✗ |
| Generative AI | ✗ | ✓ |
| Data engineering | ✓ | ✓ |
| Staff augmentation | ✗ | ✓ |
Tech stack comparison: Oxagile vs EPAM Systems
| Framework / platform | Oxagile | EPAM Systems |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| Scikit-Learn | N/A | N/A |
| LangChain | N/A | N/A |
| AWS SageMaker | N/A | ✓ |
| Azure ML | N/A | ✓ |
| GCP Vertex AI | N/A | N/A |
| Kubernetes | ✓ | ✓ |
| Apache Spark | N/A | ✓ |
| MLflow | N/A | ✓ |
Pricing comparison: Oxagile vs EPAM Systems
| Criterion | Oxagile | EPAM Systems |
|---|---|---|
| Minimum engagement | $25K | $50K |
| Engagement models | Fixed project, T&M, Dedicated team | Dedicated team, T&M, Fixed project, Staff augmentation |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Oxagile vs EPAM Systems
| Dimension | Oxagile | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | media, advertising, retail | financial services, healthcare, retail |
| Best use cases | Video content analysis ML for content moderation, tagging, or recommendation, Computer vision model development for sports performance analysis | Global enterprise AI transformation programme requiring multi-country deployment and governance, Complex Fortune 500 ML programme integrating across dozens of legacy systems |
| Typical project type | Fixed project | Dedicated team |
Oxagile vs EPAM Systems: pros and cons
| Oxagile | |
|---|---|
| + | 20+ years of video technology expertise is a genuinely rare differentiator in the ML market |
| + | NVIDIA CUDA expertise for GPU-accelerated video ML inference at production scale |
| + | AdTech ML specialization for audience targeting and real-time bidding optimization models |
| + | WebRTC and live video stream processing capability alongside batch video analysis |
| + | Eastern European delivery with New York client-facing presence |
| - | Video-first specialization means less breadth for non-video ML use cases |
| - | Less generative AI LLM tooling depth compared to AI-first firms |
| - | Limited public case studies outside media, AdTech, and sports verticals |
| EPAM Systems | |
|---|---|
| + | 62,000+ engineers provides unmatched scale for simultaneous large-scale enterprise ML programmes |
| + | Publicly traded NYSE company with audited financials — maximum organizational stability and governance |
| + | Global delivery across 50+ countries enables ML delivery under local data sovereignty requirements |
| + | Full AI lifecycle from strategy through production MLOps within one organizational relationship |
| + | Fortune 500 client base validates enterprise-grade ML delivery at the highest complexity level |
| - | Enterprise scale means ML projects go through larger organizational process — slower initiation than boutiques |
| - | High minimum engagement ($50K) limits accessibility for SMBs or early-stage organizations |
| - | Generalist technology engineering scope means ML specialist depth may be lower per individual than pure-play ML boutiques |
Who should choose Oxagile?
Oxagile is the right choice for media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise.
20+ years of video domain expertise uniquely positions Oxagile for ML use cases involving video understanding, visual search, and real-time video analytics. Minimum engagement starts at $25K. Works best with clients in media, advertising, retail, sports, healthcare.
Who should choose EPAM Systems?
EPAM Systems is the right choice for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.
62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes. Minimum engagement starts at $50K. Works best with clients in financial services, healthcare, retail, media, government.
Decision matrix: Oxagile vs EPAM Systems
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Oxagile |
| You need a large dedicated team for an ongoing programme | Oxagile |
| Your budget is at the lower end | Oxagile |
| You need specialist depth in a specific vertical | Oxagile |
| You need staff augmentation or team extension | EPAM Systems |
| You need consulting before committing to a build | Oxagile |
Use case fit: Oxagile vs EPAM Systems
| Use case | Oxagile fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Video content analysis ML for content moderation, tagging, or recommendation | Strong | Limited | Oxagile |
| Computer vision model development for sports performance analysis | Strong | Limited | Oxagile |
| Global enterprise AI transformation programme requiring multi-country deployment and governance | Limited | Strong | EPAM Systems |
| Complex Fortune 500 ML programme integrating across dozens of legacy systems | Limited | Strong | EPAM Systems |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Oxagile vs EPAM Systems
EPAM Systems (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes. It is best for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.
Oxagile (3.8/5) is the better choice when media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise. If your situation matches those criteria, Oxagile is a competitive option.
Related comparisons
Oxagile vs EPAM Systems FAQ
Is Oxagile better than EPAM Systems?
EPAM Systems (3.9/5) scores higher overall, but "better" depends on your use case. Oxagile is better for media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise. EPAM Systems is better for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.
How do Oxagile and EPAM Systems differ in pricing?
Oxagile uses fixed project, t&m, dedicated team pricing with a minimum engagement of $25K. EPAM Systems uses dedicated team, t&m, fixed project, staff augmentation pricing with a minimum engagement of $50K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Oxagile or EPAM Systems?
Oxagile 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 Oxagile and EPAM Systems?
Oxagile's primary differentiator is: 20+ years of video domain expertise uniquely positions oxagile for ml use cases involving video understanding, visual search, and real-time video analytics. EPAM Systems's primary differentiator is: 62,000+ engineers across 50+ countries delivering ml inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise ai programmes. They also differ in team size (250–500 vs 62,000+), minimum engagement ($25K vs $50K), and primary industries served (media, advertising vs financial services, healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.