EPAM Systems vs 10Clouds: full comparison for 2026
Quick verdict
EPAM Systems (4.1/5) edges ahead of 10Clouds (3.8/5) overall. EPAM Systems is the better choice for enterprises wanting generative AI consulting paired directly with engineering delivery. 10Clouds is the stronger option for product teams wanting generative AI strategy folded into UX and design. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs 10Clouds: head-to-head summary
| Criterion | EPAM Systems | 10Clouds |
|---|---|---|
| Founded | 1993 | 2009 |
| HQ | Newtown, United States | Warsaw, Poland |
| Team size | 62,000+ | 51-200 |
| Rating | 4.1 / 5 | 3.8 / 5 |
| Primary differentiator | Engineering-heavy consulting model, pairing generative AI strategists with the technical build team | Generative AI consulting treated as one integrated capability inside full product design |
| Pricing model | Retainer or dedicated team, enterprise contracting | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, AWS, Azure | Python, React, Node.js |
| Industries served | Financial services, Healthcare, Retail & e-commerce, Media & entertainment | Fintech, Healthcare, Retail & e-commerce |
EPAM Systems vs 10Clouds: overview
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. Generative AI advisory and transformation engineering is a marketed practice area, distinguished from pure Big Four strategy shops by EPAM's engineering-heavy delivery model, pairing generative AI advisors directly with the technical staff who build the resulting systems.
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 consulting treated as an integrated capability rather than a standalone service line.
Services and capabilities: EPAM Systems vs 10Clouds
| Capability | EPAM Systems | 10Clouds |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✓ | ✗ |
| Machine learning | ✓ | ✓ |
| Data engineering | ✗ | ✓ |
| MLOps | ✓ | ✗ |
| Fixed-price projects | ✗ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: EPAM Systems vs 10Clouds
| Framework / platform | EPAM Systems | 10Clouds |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: EPAM Systems vs 10Clouds
| Criterion | EPAM Systems | 10Clouds |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Dedicated team, Retainer | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs 10Clouds
| Dimension | EPAM Systems | 10Clouds |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Healthcare, Retail & e-commerce | Fintech, Healthcare, Retail & e-commerce |
| Best use cases | Running a generative AI strategy engagement that needs to transition directly into technical build with the same team., Needing a publicly-traded vendor for audit or procurement compliance reasons. | Getting generative AI strategy input at the same time a product's UX gets redesigned., Adding generative AI consulting to an existing web or mobile product roadmap. |
| Typical project type | Dedicated team | Fixed project |
EPAM Systems vs 10Clouds: pros and cons
| EPAM Systems | |
|---|---|
| + | Public-company financial disclosure that no private consultancy on this list can match. |
| + | Engineering-heavy delivery model avoids the strategy-to-build handoff gap common at pure consultancies. |
| + | Scale to staff several large generative AI consulting and build programs across regions simultaneously. |
| + | S&P 500 membership lets enterprise procurement teams vet it through standard due diligence. |
| - | Generative AI consulting sits inside an enormous engineering business rather than functioning as a dedicated specialty |
| - | Scale generally means slower onboarding and higher minimum engagement than boutique firms |
| 10Clouds | |
|---|---|
| + | Strong product design and UX practice means generative AI strategy recommendations arrive with real implementation context. |
| + | Fifteen-plus years of operating history in the Warsaw tech scene. |
| + | Comfortable across the full product stack, not just the generative AI layer. |
| + | Mid-size team keeps senior engineers involved on most engagements. |
| - | Generative AI consulting sits alongside, not ahead of, the firm's core product design business |
| - | Less AI-specific case-study depth than firms built around generative AI from founding |
Who should choose EPAM Systems?
A typical fit: running a generative AI strategy engagement that needs to transition directly into technical build with the same team.
Engineering-heavy consulting model, pairing generative AI strategists with the technical build team. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media & entertainment.
Who should choose 10Clouds?
A typical fit: getting generative AI strategy input at the same time a product's UX gets redesigned.
Generative AI consulting 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.
Decision matrix: EPAM Systems vs 10Clouds
| 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 | EPAM Systems |
| Your budget is at the lower end | Compare: EPAM Systems (Not disclosed) vs 10Clouds (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: EPAM Systems vs 10Clouds
| Use case | EPAM Systems fit | 10Clouds fit | Winner |
|---|---|---|---|
| Running a generative AI strategy engagement that needs to transition directly into technical build with the same team. | Strong | Strong | Both equally |
| Needing a publicly-traded vendor for audit or procurement compliance reasons. | Strong | Limited | EPAM Systems |
| Getting generative AI strategy input at the same time a product's UX gets redesigned. | Limited | Strong | 10Clouds |
| Adding generative AI consulting to an existing web or mobile product roadmap. | Limited | Strong | 10Clouds |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: EPAM Systems vs 10Clouds
EPAM Systems (4.1/5) is the stronger overall choice for most Generative AI Consulting projects. Engineering-heavy consulting model, pairing generative AI strategists with the technical build team.
10Clouds (3.8/5) is worth a look if you need adding generative AI consulting to an existing web or mobile product roadmap. If your situation matches that, 10Clouds is a competitive option.
Related comparisons
EPAM Systems vs 10Clouds FAQ
Is EPAM Systems better than 10Clouds?
EPAM Systems (4.1/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: public-company financial disclosure that no private consultancy on this list can match. 10Clouds's strongest advantage: strong product design and UX practice means generative AI strategy recommendations arrive with real implementation context.
How do EPAM Systems and 10Clouds differ in pricing?
EPAM Systems uses retainer or dedicated team, enterprise contracting pricing. 10Clouds uses fixed project or dedicated team 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 10Clouds?
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 firm before shortlisting.
What are the main differences between EPAM Systems and 10Clouds?
EPAM Systems's primary differentiator is: engineering-heavy consulting model, pairing generative AI strategists with the technical build team. 10Clouds's primary differentiator is: generative AI consulting treated as one integrated capability inside full product design. They also differ in team size (62,000+ vs 51-200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Fintech, Healthcare).
Verify all details directly with each firm before making a decision.