Andersen vs 10Clouds: full comparison for 2026
Quick verdict
Andersen (4.0/5) edges ahead of 10Clouds (3.8/5) overall. Andersen is the better choice for enterprises wanting AI advisory paired with broad platform engineering. 10Clouds is the stronger option for product teams wanting AI strategy folded into UX and design. The right choice depends on your project size, budget, and required tech stack.
Andersen vs 10Clouds: head-to-head summary
| Criterion | Andersen | 10Clouds |
|---|---|---|
| Founded | 2007 | 2009 |
| HQ | Warsaw, Poland | Warsaw, Poland |
| Team size | 3,500+ | 51-200 |
| Rating | 4.0 / 5 | 3.8 / 5 |
| Primary differentiator | 3,500-plus specialists across 20 global offices with a named AI advisory practice | AI advisory treated as one integrated capability inside full product design |
| Pricing model | Dedicated team or retainer | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, .NET, Java | Python, React, Node.js |
| Industries served | Financial services, Healthcare, Logistics, Automotive | Fintech, Healthcare, Retail & e-commerce |
Andersen vs 10Clouds: overview
Andersen
Andersen was founded in 2007 and is headquartered in Warsaw, Poland, running more than 3,500 specialists across 20 office locations and 16 development centers globally. Its named AI and data practice spans AI advisory, machine learning, data engineering, and robotic process integration, layered on top of a broader stack covering .NET, Java, Python, PHP, and Go. Client industries include financial services, healthcare, logistics, automotive, and media.
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 agency's core business is digital product consultancy, web and mobile development, and UX design, with AI advisory treated as an integrated capability rather than a standalone service line.
Services and capabilities: Andersen vs 10Clouds
| Capability | Andersen | 10Clouds |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| Data engineering | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Fixed-price projects | ✗ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Andersen vs 10Clouds
| Framework / platform | Andersen | 10Clouds |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: Andersen vs 10Clouds
| Criterion | Andersen | 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: Andersen vs 10Clouds
| Dimension | Andersen | 10Clouds |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Healthcare, Logistics | Fintech, Healthcare, Retail & e-commerce |
| Best use cases | Running an AI advisory initiative that needs to plug into an existing multi-technology enterprise stack., Adding robotic process integration alongside an AI advisory engagement. | Getting AI strategy input at the same time a product's UX gets redesigned., Adding AI advisory to an existing web or mobile product roadmap. |
| Typical project type | Dedicated team | Fixed project |
Andersen vs 10Clouds: pros and cons
| Andersen | |
|---|---|
| + | A large global footprint, 20 offices and 16 development centers, supports concurrent enterprise programs. |
| + | The named AI and data practice isn't a generic add-on to broader software services. |
| + | Nearly two decades of software delivery history spanning multiple technology stacks. |
| + | Vertical coverage runs across financial services, healthcare, logistics, and automotive. |
| - | AI advisory is one practice area within a much larger, multi-stack engineering business |
| - | Scale typically means a more formal sales and onboarding process than boutique agencies |
| 10Clouds | |
|---|---|
| + | A strong product design and UX practice means 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 AI layer. |
| + | A mid-size team keeps senior engineers involved on most engagements. |
| - | AI advisory sits alongside, not ahead of, the agency's core product design business |
| - | Less AI-specific case-study depth than agencies built around AI from founding |
Who should choose Andersen?
A typical fit: running an AI advisory initiative that needs to plug into an existing multi-technology enterprise stack.
3,500-plus specialists across 20 global offices with a named AI advisory practice. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Logistics, Automotive.
Who should choose 10Clouds?
A typical fit: getting AI strategy input at the same time a product's UX gets redesigned.
AI advisory 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: Andersen 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 | Andersen |
| Your budget is at the lower end | Compare: Andersen (Not disclosed) vs 10Clouds (Not disclosed) |
| You need specialist depth in a specific vertical | Andersen |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Andersen |
Use case fit: Andersen vs 10Clouds
| Use case | Andersen fit | 10Clouds fit | Winner |
|---|---|---|---|
| Running an AI advisory initiative that needs to plug into an existing multi-technology enterprise stack. | Strong | Strong | Both equally |
| Adding robotic process integration alongside an AI advisory engagement. | Strong | Strong | Both equally |
| Getting AI strategy input at the same time a product's UX gets redesigned. | Limited | Strong | 10Clouds |
| Adding AI advisory to an existing web or mobile product roadmap. | Strong | Strong | Both equally |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: Andersen vs 10Clouds
Andersen (4.0/5) is the stronger overall choice for most AI Consulting projects. 3,500-plus specialists across 20 global offices with a named AI advisory practice.
10Clouds (3.8/5) is worth a look if you need adding AI advisory to an existing web or mobile product roadmap. If your situation matches that, 10Clouds is a competitive option.
Related comparisons
Andersen vs 10Clouds FAQ
Is Andersen better than 10Clouds?
Andersen (4.0/5) scores higher overall, but "better" depends on your use case. Andersen's strongest advantage: a large global footprint, 20 offices and 16 development centers, supports concurrent enterprise programs. 10Clouds's strongest advantage: a strong product design and UX practice means AI strategy recommendations arrive with real implementation context.
How do Andersen and 10Clouds differ in pricing?
Andersen uses dedicated team or retainer 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: Andersen or 10Clouds?
10Clouds is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Andersen and 10Clouds?
Andersen's primary differentiator is: 3,500-plus specialists across 20 global offices with a named AI advisory practice. 10Clouds's primary differentiator is: AI advisory treated as one integrated capability inside full product design. They also differ in team size (3,500+ 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 agency before making a decision.