STX Next vs 10Clouds: full comparison for 2026
Quick verdict
STX Next (4.2/5) edges ahead of 10Clouds (4.1/5) overall. STX Next is the better choice for python product teams adding ML capacity. 10Clouds is the stronger option for Banks, insurers and fintechs building AI features. The right choice depends on your project size, budget, and required tech stack.
STX Next vs 10Clouds: head-to-head summary
| Criterion | STX Next | 10Clouds |
|---|---|---|
| Founded | 2005 | 2009 |
| HQ | Poznań, Poland | Warsaw, Poland |
| Team size | 250–999 | 100–200 |
| Rating | 4.2 / 5 | 4.1 / 5 |
| Primary differentiator | Large Python bench with documented ML staff-augmentation work | Financial-services AI focus with Claude partner status |
| Pricing model | Time and materials; team extension; rates on request | Time and materials; fixed-term staff augmentation; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, Django, PyTorch | Python, Claude, OpenAI |
| Industries served | Real estate tech, Healthcare, Fintech, SaaS | Fintech, Banking, Insurance, SaaS |
STX Next vs 10Clouds: overview
STX Next
STX Next was founded in 2005 in Poznań, Poland, and runs delivery centers in Poland and Mexico. It describes itself as Europe's largest Python-focused engineering partner for data, AI and cloud (per company website; independently unverifiable), and Clutch places it in the 250–999 employee band. A Clutch review covers a 2023–2024 staff-augmentation engagement for a real-estate technology client involving machine learning, computer vision and recommendation systems. Other reviews describe multi-year Python team extensions.
10Clouds
10Clouds was founded in 2009 in Warsaw by Maciej Cielecki and others, and employs somewhere between 100 and 200 people depending on the source. It keeps an in-house product team and also supplies developers or designers to clients for fixed periods, a model it has used with U.S. clients such as Rippling. In 2026 it announced a merger with 10Clouds Financial Institutions, creating an AI unit for banks, insurers and fintechs, and it is a Select partner in the Claude Partner Network services track.
Services and capabilities: STX Next vs 10Clouds
| Capability | STX Next | 10Clouds |
|---|---|---|
| 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: STX Next vs 10Clouds
| Framework / platform | STX Next | 10Clouds |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | ✓ |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: STX Next vs 10Clouds
| Criterion | STX Next | 10Clouds |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: STX Next vs 10Clouds
| Dimension | STX Next | 10Clouds |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Real estate tech, Healthcare, Fintech | Fintech, Banking, Insurance |
| Best use cases | Adding a recommendation-systems engineer to a marketplace product, Extending a Python team with a computer-vision specialist | Adding an agent developer to a bank's internal automation team, Staffing an LLM engineer for an insurer's claims product |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
STX Next vs 10Clouds: pros and cons
| STX Next | |
|---|---|
| + | Python depth means ML and backend roles come from one bench |
| + | Documented multi-year team extensions |
| + | Mexico center adds U.S. time-zone coverage |
| - | AI is a practice within a broader Python services company |
| - | Largest-in-Europe positioning is the company's own claim |
| - | No public rates |
| 10Clouds | |
|---|---|
| + | Clear industry focus on regulated financial services |
| + | Claude Partner Network status for teams building on Anthropic models |
| + | Has worked as an embedded team for U.S. scale-ups |
| - | The 2026 merger means leadership and structure are still settling |
| - | Small bench for large placements |
| - | Rates not published |
Who should choose STX Next?
A typical fit: adding a recommendation-systems engineer to a marketplace product.
Large Python bench with documented ML staff-augmentation work. Minimum engagement is not publicly disclosed. Works best with clients in Real estate tech, Healthcare, Fintech, SaaS.
Who should choose 10Clouds?
A typical fit: adding an agent developer to a bank's internal automation team.
Financial-services AI focus with Claude partner status. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Banking, Insurance, SaaS.
Decision matrix: STX Next vs 10Clouds
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | STX Next |
| Your budget is at the lower end | Compare: STX Next (Not disclosed) vs 10Clouds (Not disclosed) |
| You need specialist depth in a specific vertical | STX Next |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: STX Next vs 10Clouds
| Use case | STX Next fit | 10Clouds fit | Winner |
|---|---|---|---|
| Adding a recommendation-systems engineer to a marketplace product | Strong | Strong | Both equally |
| Extending a Python team with a computer-vision specialist | Strong | Limited | STX Next |
| Adding an agent developer to a bank's internal automation team | Strong | Strong | Both equally |
| Staffing an LLM engineer for an insurer's claims product | Limited | Strong | 10Clouds |
Verdict: STX Next vs 10Clouds
STX Next (4.2/5) is the stronger overall choice for most AI Staffing projects. Large Python bench with documented ML staff-augmentation work.
10Clouds (4.1/5) is worth a look if you need staffing an LLM engineer for an insurer's claims product. If your situation matches that, 10Clouds is a competitive option.
Related comparisons
STX Next vs 10Clouds FAQ
Is STX Next better than 10Clouds?
STX Next (4.2/5) scores higher overall, but "better" depends on your use case. STX Next's strongest advantage: python depth means ML and backend roles come from one bench. 10Clouds's strongest advantage: clear industry focus on regulated financial services.
How do STX Next and 10Clouds differ in pricing?
STX Next uses time and materials; team extension; rates on request pricing. 10Clouds uses time and materials; fixed-term staff augmentation; 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: STX Next or 10Clouds?
STX Next 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 STX Next and 10Clouds?
STX Next's primary differentiator is: large Python bench with documented ML staff-augmentation work. 10Clouds's primary differentiator is: financial-services AI focus with Claude partner status. They also differ in team size (250–999 vs 100–200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Real estate tech, Healthcare vs Fintech, Banking).
Verify all details directly with each agency before making a decision.