STX Next vs Siili Solutions: full comparison for 2026
Last updated: July 2026
Quick verdict
STX Next (4.3/5) edges ahead of Siili Solutions (3.7/5) overall. STX Next is the better choice for companies needing ML development paired with deep, large-scale Python software engineering capacity. Siili Solutions is the stronger option for nordic and European enterprises wanting a publicly listed, financially transparent IT consultancy partner. The right choice depends on your project size, budget, and required tech stack.
STX Next vs Siili Solutions: head-to-head summary
| Criterion | STX Next | Siili Solutions |
|---|---|---|
| Founded | 2005 | 2005 |
| HQ | Poznan, Poland | Helsinki, Finland |
| Team size | 201–500 | 501–1000 |
| Rating | 4.3 / 5 | 3.7 / 5 |
| Best for | Companies needing ML development paired with deep, large-scale Python software engineering capacity | Nordic and European enterprises wanting a publicly listed, financially transparent IT consultancy partner |
| Pricing model | Dedicated team, staff augmentation, fixed project | Dedicated team, retainer, fixed project |
| Min. engagement | $25K | $30K |
| Primary tech stack | Python, Django, FastAPI | Python, Java, AWS |
| Industries served | SaaS, Fintech, Healthcare, E-commerce, Enterprise | Enterprise, Telecommunications, Financial Services, Retail |
STX Next vs Siili Solutions: overview
STX Next
STX Next, founded in March 2005 in Poznan, Poland, grew from an 8-person startup into a nearly 500-person Python engineering firm with delivery centers across Poland and Mexico. Known primarily as one of Europe's largest dedicated Python engineering companies, STX Next has built out AI/ML and data engineering practices on top of its deep Python bench, making it a strong generalist option for ML projects that also require broader software engineering.
Siili Solutions
Siili Solutions Oyj, founded in 2005 and headquartered in Helsinki, Finland, is a publicly listed IT consultancy on Nasdaq Helsinki (ticker SIILI) with 500 to over 1,000 employees across 19 locations. Siili offers software development, digital transformation, and machine learning services, and expanded its AI and digital product capabilities in part through its 2020 acquisition of Budapest-based Supercharge, disclosed here as an ownership change affecting Siili's broader group structure.
Services and capabilities: STX Next vs Siili Solutions
| Capability | STX Next | Siili Solutions |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✓ | ✗ |
Tech stack comparison: STX Next vs Siili Solutions
| Framework / platform | STX Next | Siili Solutions |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: STX Next vs Siili Solutions
| Criterion | STX Next | Siili Solutions |
|---|---|---|
| Minimum engagement | $25K | $30K |
| Engagement models | Dedicated team, Staff augmentation, Fixed project | Dedicated team, Retainer, Fixed project |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: STX Next vs Siili Solutions
| Dimension | STX Next | Siili Solutions |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, Healthcare | Enterprise, Telecommunications, Financial Services |
| Best use cases | ML feature development inside a larger Python software platform, Scaling an engineering team with dedicated Python and ML staff | Enterprise digital transformation with an ML component, Nordic-region software development and data engineering |
| Typical project type | Dedicated team | Dedicated team |
STX Next vs Siili Solutions: pros and cons
| STX Next | |
|---|---|
| + | Two decades of operating history since founding in 2005 with proven scale of roughly 500 engineers |
| + | Deep Python engineering bench supports complex ML and software integration projects |
| + | Multiple delivery centers across Poland and Mexico for coverage flexibility |
| + | Established staff augmentation model for teams needing to scale quickly |
| - | ML and AI is one practice among several rather than the firm's sole focus |
| - | Larger organizational size may mean less founder-level attention than boutique specialists |
| - | Best fit skews toward Python-centric stacks rather than polyglot ML environments |
| Siili Solutions | |
|---|---|
| + | Publicly listed on Nasdaq Helsinki, providing financial transparency and stability signals |
| + | Two decades of operating history since founding in 2005, with a large, established Nordic footprint |
| + | 19 office locations support broad European coverage and delivery flexibility |
| + | Expanded AI and digital product capability via its 2020 acquisition of Supercharge in Budapest |
| - | AI and ML is one practice within a much broader generalist IT consultancy portfolio |
| - | 2020 acquisition of Supercharge represents a group ownership change worth understanding before engaging that subsidiary specifically |
| - | Larger public-company structure may mean less flexibility than privately held boutiques |
Who should choose STX Next?
STX Next is the right choice for companies needing ML development paired with deep, large-scale Python software engineering capacity.
One of Europe's largest dedicated Python engineering companies, with ML and data practices built on that scale. Minimum engagement starts at $25K. Works best with clients in SaaS, Fintech, Healthcare, E-commerce, Enterprise.
Who should choose Siili Solutions?
Siili Solutions is the right choice for nordic and European enterprises wanting a publicly listed, financially transparent IT consultancy partner.
Publicly traded on Nasdaq Helsinki, offering financial transparency uncommon among privately held ML firms. Minimum engagement starts at $30K. Works best with clients in Enterprise, Telecommunications, Financial Services, Retail.
Decision matrix: STX Next vs Siili Solutions
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | STX Next |
| You need a large dedicated team for an ongoing programme | STX Next |
| Your budget is at the lower end | STX Next |
| You need specialist depth in a specific vertical | STX Next |
| You need staff augmentation or team extension | STX Next |
| You need consulting before committing to a build | STX Next |
Use case fit: STX Next vs Siili Solutions
| Use case | STX Next fit | Siili Solutions fit | Winner |
|---|---|---|---|
| ML feature development inside a larger Python software platform | Strong | Strong | Both equally |
| Scaling an engineering team with dedicated Python and ML staff | Strong | Limited | STX Next |
| Enterprise digital transformation with an ML component | Strong | Strong | Both equally |
| Nordic-region software development and data engineering | Limited | Strong | Siili Solutions |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Strong | Limited | STX Next |
Verdict: STX Next vs Siili Solutions
STX Next (4.3/5) is the stronger overall choice for most Machine Learning Development projects. One of Europe's largest dedicated Python engineering companies, with ML and data practices built on that scale. It is best for companies needing ML development paired with deep, large-scale Python software engineering capacity.
Siili Solutions (3.7/5) is the better choice when nordic and European enterprises wanting a publicly listed, financially transparent IT consultancy partner. If your situation matches those criteria, Siili Solutions is a competitive option.
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STX Next vs Siili Solutions FAQ
Is STX Next better than Siili Solutions?
STX Next (4.3/5) scores higher overall, but "better" depends on your use case. STX Next is better for companies needing ML development paired with deep, large-scale Python software engineering capacity. Siili Solutions is better for nordic and European enterprises wanting a publicly listed, financially transparent IT consultancy partner.
How do STX Next and Siili Solutions differ in pricing?
STX Next uses dedicated team, staff augmentation, fixed project pricing with a minimum engagement of $25K. Siili Solutions uses dedicated team, retainer, fixed project pricing with a minimum engagement of $30K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: STX Next or Siili Solutions?
Siili Solutions 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 STX Next and Siili Solutions?
STX Next's primary differentiator is: one of europe's largest dedicated python engineering companies, with ml and data practices built on that scale. Siili Solutions's primary differentiator is: publicly traded on nasdaq helsinki, offering financial transparency uncommon among privately held ml firms. They also differ in team size (201–500 vs 501–1000), minimum engagement ($25K vs $30K), and primary industries served (SaaS, Fintech vs Enterprise, Telecommunications).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.