EPAM Systems vs Xenoss: full comparison for 2026
Quick verdict
EPAM Systems (4.6/5) edges ahead of Xenoss (3.8/5) overall. EPAM Systems is the better choice for large enterprises, regulated industries, multi-team AI programs. Xenoss is the stronger option for AdTech and MarTech firms needing real-time data plus AI. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs Xenoss: head-to-head summary
| Criterion | EPAM Systems | Xenoss |
|---|---|---|
| Founded | 1993 | 2013 |
| HQ | Newtown, Pennsylvania, USA | New York, New York, USA |
| Team size | 61,000+ | 100–200 |
| Rating | 4.6 / 5 | 3.8 / 5 |
| Primary differentiator | Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes | Real-time, high-load data engineering from AdTech roots |
| Pricing model | Time and materials for augmented engineers; dedicated team and managed program contracts; rates on request | Team extension and project pricing; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Kafka, Spark |
| Industries served | Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing | Media, Retail & e-commerce, Software & SaaS |
EPAM Systems vs Xenoss: overview
EPAM Systems
EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with roughly 61,000 employees across delivery centers in Europe, the Americas and Asia. It is a public company listed on the New York Stock Exchange. On its Q2 2026 earnings call, management said EPAM had more than 5,700 Anthropic-certified engineers and was among the five largest certified partners worldwide, with AI-native work making up about 11% of revenue. EPAM employs its engineers directly and sells them as augmented capacity, dedicated teams or managed programs, though most large accounts end up in the managed model.
Xenoss
Xenoss was founded in 2013 by AdTech veterans and lists its headquarters in New York, with CEO Dmitry Sverdlik. Directories put headcount between 100 and 200. It specializes in AI and data engineering, including AI agents, real-time data systems and LLM knowledge bases, and favors small senior teams. Team extension appears in its history, but it does not run a dedicated staff augmentation offer.
Services and capabilities: EPAM Systems vs Xenoss
| Capability | EPAM Systems | Xenoss |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| MLOps & deployment | ✓ | ✗ |
| Computer vision | ✗ | ✗ |
| Data engineering | ✓ | ✓ |
| AI agent development | ✓ | ✓ |
| Fractional / part-time experts | ✗ | ✗ |
| Risk-free trial period | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
Tech stack comparison: EPAM Systems vs Xenoss
| Framework / platform | EPAM Systems | Xenoss |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: EPAM Systems vs Xenoss
| Criterion | EPAM Systems | Xenoss |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs Xenoss
| Dimension | EPAM Systems | Xenoss |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Financial services, Healthcare & life sciences, Retail & e-commerce | Media, Retail & e-commerce, Software & SaaS |
| Best use cases | Adding a 15-person GenAI squad to a bank's existing platform team, Rolling out agentic workflows across several business units under one master agreement | Adding real-time feature engineering for a bidding model, Building an LLM knowledge base on marketing data |
| Typical project type | Full-time dedicated engineers | Dedicated team |
EPAM Systems vs Xenoss: pros and cons
| EPAM Systems | |
|---|---|
| + | A Q2 2026 earnings call put its Anthropic-certified engineer count above 5,700, the largest verified GenAI bench on this list |
| + | Public-company reporting, audited financials and mature security reviews make vendor onboarding easier at banks and insurers |
| + | Can staff ten or more AI engineers in parallel across several time zones without running out of senior people |
| + | Deep data-platform practice means LLM work and the data engineering under it can come from one supplier |
| - | Rates are among the highest on this list and are only shared after scoping |
| - | Small requests for one or two engineers rarely get the same attention as large programs |
| - | Engagements tend to drift toward managed delivery, which moves decisions away from your own team |
| Xenoss | |
|---|---|
| + | High-load, real-time data experience |
| + | Small senior teams with low management overhead |
| + | Builds agents and knowledge bases on its own data work |
| - | No dedicated staff augmentation page |
| - | Industry focus is narrow outside AdTech and MarTech |
| - | Headcount data varies |
Who should choose EPAM Systems?
A typical fit: adding a 15-person GenAI squad to a bank's existing platform team.
Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing.
Who should choose Xenoss?
A typical fit: adding real-time feature engineering for a bidding model.
Real-time, high-load data engineering from AdTech roots. Minimum engagement is not publicly disclosed. Works best with clients in Media, Retail & e-commerce, Software & SaaS.
Decision matrix: EPAM Systems vs Xenoss
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; EPAM Systems rates higher overall |
| You want the supplier to own delivery as well as staffing | Both; EPAM Systems rates higher overall |
| You need one expert part-time | Neither lists part-time experts; ask about reduced hours |
| You want to test an engineer before signing for months | Neither publishes a trial; ask for a short first term |
| Your budget is at the lower end | Compare: EPAM Systems (Not published) vs Xenoss (Not published) |
| You need overlap with U.S. working hours | Neither is nearshore; agree overlap hours up front |
| You need specialist depth in a specific vertical | EPAM Systems |
Use case fit: EPAM Systems vs Xenoss
| Use case | EPAM Systems fit | Xenoss fit | Winner |
|---|---|---|---|
| Adding a 15-person GenAI squad to a bank's existing platform team | Strong | Strong | Both equally |
| Rolling out agentic workflows across several business units under one master agreement | Strong | Limited | EPAM Systems |
| Adding real-time feature engineering for a bidding model | Strong | Strong | Both equally |
| Building an LLM knowledge base on marketing data | Limited | Strong | Xenoss |
Verdict: EPAM Systems vs Xenoss
EPAM Systems (4.6/5) is the stronger overall choice for most AI Staff Augmentation projects. Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes.
Xenoss (3.8/5) is worth a look if you need building an LLM knowledge base on marketing data. If your situation matches that, Xenoss is a competitive option.
Related comparisons
EPAM Systems vs Xenoss FAQ
Is EPAM Systems better than Xenoss?
EPAM Systems (4.6/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: a Q2 2026 earnings call put its Anthropic-certified engineer count above 5,700, the largest verified GenAI bench on this list. Xenoss's strongest advantage: High-load, real-time data experience.
How do EPAM Systems and Xenoss differ in pricing?
EPAM Systems uses time and materials for augmented engineers; dedicated team and managed program contracts; rates on request pricing. Xenoss uses team extension and project pricing; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: EPAM Systems or Xenoss?
Xenoss 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 EPAM Systems and Xenoss?
EPAM Systems's primary differentiator is: thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes. Xenoss's primary differentiator is: Real-time, high-load data engineering from AdTech roots. They also differ in team size (61,000+ vs 100–200), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Healthcare & life sciences vs Media, Retail & e-commerce).
Verify all details directly with each company before making a decision.