10Clouds vs EPAM Systems: full comparison for 2026
Quick verdict
EPAM Systems (4.1/5) edges ahead of 10Clouds (4.0/5) overall. EPAM Systems is the better choice for global enterprises running generative AI at massive scale. 10Clouds is the stronger option for product teams wanting generative AI folded into UX and design. The right choice depends on your project size, budget, and required tech stack.
10Clouds vs EPAM Systems: head-to-head summary
| Criterion | 10Clouds | EPAM Systems |
|---|---|---|
| Founded | 2009 | 1993 |
| HQ | Warsaw, Poland | Newtown, United States |
| Team size | 51-200 | 62,000+ |
| Rating | 4.0 / 5 | 4.1 / 5 |
| Primary differentiator | Generative AI treated as one integrated capability inside full product design | Public-company scale (NYSE: EPAM) with financial transparency few competitors offer |
| Pricing model | Fixed project or dedicated team | Retainer or dedicated team, enterprise contracting |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, OpenAI API, React | Python, OpenAI API, AWS |
| Industries served | Fintech, Healthcare, Retail & e-commerce | Financial services, Healthcare, Retail & e-commerce, Media & entertainment |
10Clouds vs EPAM Systems: overview
10Clouds
10Clouds has run out of Warsaw, Poland since 2009, with a headcount reported around 176 as of mid-2024 against a wider LinkedIn range of 51-200. The firm's core business is digital product consultancy, web and mobile development, and UX design, with generative AI treated as an integrated capability rather than a standalone service line. That framing suits clients who want generative AI embedded into a product experience someone else is also designing.
EPAM Systems
EPAM Systems dates to 1993, co-founded in New Jersey and Minsk by Arkadiy Dobkin and Leo Lozner, and has traded on the NYSE as an S&P 500 constituent since 2012. It employed roughly 62,850 people across more than 55 countries at the end of 2025, a scale category no other agency on this list approaches. Generative AI transformation engineering is a marketed practice area, but at this size it functions as part of a much larger digital engineering business rather than a standalone specialty.
Services and capabilities: 10Clouds vs EPAM Systems
| Capability | 10Clouds | EPAM Systems |
|---|---|---|
| Generative AI | ✓ | ✓ |
| Machine learning | ✓ | ✗ |
| AI agents | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| AI consulting | ✗ | ✓ |
| Fixed-price projects | ✓ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: 10Clouds vs EPAM Systems
| Framework / platform | 10Clouds | EPAM Systems |
|---|---|---|
| Python | ✓ | ✓ |
| OpenAI API | ✓ | ✓ |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: 10Clouds vs EPAM Systems
| Criterion | 10Clouds | EPAM Systems |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Dedicated team | Dedicated team, Retainer |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: 10Clouds vs EPAM Systems
| Dimension | 10Clouds | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Healthcare, Retail & e-commerce | Financial services, Healthcare, Retail & e-commerce |
| Best use cases | Redesigning a product's UX at the same time a generative AI feature gets built into it., Adding generative AI to an existing web or mobile product without hiring a separate vendor. | Running a generative AI transformation program spanning multiple business units and regions., Needing a publicly-traded vendor for audit or procurement compliance reasons. |
| Typical project type | Fixed project | Dedicated team |
10Clouds vs EPAM Systems: pros and cons
| 10Clouds | |
|---|---|
| + | Strong product design and UX practice means generative AI features arrive inside a polished product. |
| + | Fifteen-plus years of operating history in the Warsaw tech scene. |
| + | Comfortable across the full product stack, not just the AI layer. |
| + | Mid-size team keeps senior engineers involved on most engagements. |
| - | Generative AI sits alongside, not ahead of, the firm's core product design business |
| - | Less AI-specific case-study depth than agencies built around AI from founding |
| EPAM Systems | |
|---|---|
| + | Public-company financial disclosure that no private agency on this list can match. |
| + | Scale to staff several large generative AI programs across regions simultaneously. |
| + | S&P 500 membership lets enterprise procurement teams vet it through standard due diligence. |
| + | Partnerships span all three major cloud hyperscalers. |
| - | Generative AI sits inside an enormous engineering business rather than as a dedicated specialty |
| - | Scale generally means slower onboarding and higher minimum engagement than boutique firms |
Who should choose 10Clouds?
A typical fit: redesigning a product's UX at the same time a generative AI feature gets built into it.
Generative AI treated as one integrated capability inside full product design. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Healthcare, Retail & e-commerce.
Who should choose EPAM Systems?
A typical fit: running a generative AI transformation program spanning multiple business units and regions.
Public-company scale (NYSE: EPAM) with financial transparency few competitors offer. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media & entertainment.
Decision matrix: 10Clouds vs EPAM Systems
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | 10Clouds |
| You need a large dedicated team for an ongoing programme | 10Clouds |
| Your budget is at the lower end | Compare: 10Clouds (Not disclosed) vs EPAM Systems (Not disclosed) |
| You need specialist depth in a specific vertical | EPAM Systems |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | EPAM Systems |
Use case fit: 10Clouds vs EPAM Systems
| Use case | 10Clouds fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Redesigning a product's UX at the same time a generative AI feature gets built into it. | Strong | Limited | 10Clouds |
| Adding generative AI to an existing web or mobile product without hiring a separate vendor. | Strong | Limited | 10Clouds |
| Running a generative AI transformation program spanning multiple business units and regions. | Strong | Strong | Both equally |
| Needing a publicly-traded vendor for audit or procurement compliance reasons. | Limited | Strong | EPAM Systems |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: 10Clouds vs EPAM Systems
EPAM Systems (4.1/5) is the stronger overall choice for most Generative AI Development projects. Public-company scale (NYSE: EPAM) with financial transparency few competitors offer.
10Clouds (4.0/5) is worth a look if you need adding generative AI to an existing web or mobile product without hiring a separate vendor. If your situation matches that, 10Clouds is a competitive option.
Related comparisons
10Clouds vs EPAM Systems FAQ
Is 10Clouds better than EPAM Systems?
EPAM Systems (4.1/5) scores higher overall, but "better" depends on your use case. 10Clouds's strongest advantage: strong product design and UX practice means generative AI features arrive inside a polished product. EPAM Systems's strongest advantage: public-company financial disclosure that no private agency on this list can match.
How do 10Clouds and EPAM Systems differ in pricing?
10Clouds uses fixed project or dedicated team pricing. EPAM Systems uses retainer or dedicated team, enterprise contracting pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: 10Clouds or EPAM Systems?
EPAM Systems 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 10Clouds and EPAM Systems?
10Clouds's primary differentiator is: generative AI treated as one integrated capability inside full product design. EPAM Systems's primary differentiator is: public-company scale (NYSE: EPAM) with financial transparency few competitors offer. They also differ in team size (51-200 vs 62,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Fintech, Healthcare vs Financial services, Healthcare).
Verify all details directly with each company before making a decision.