STX Next vs SDG Group: full comparison for 2026
Last updated: July 2026
Quick verdict
STX Next (4.3/5) edges ahead of SDG Group (3.7/5) overall. STX Next is the better choice for companies needing ML development paired with deep, large-scale Python software engineering capacity. SDG Group is the stronger option for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme. The right choice depends on your project size, budget, and required tech stack.
STX Next vs SDG Group: head-to-head summary
| Criterion | STX Next | SDG Group |
|---|---|---|
| Founded | 2005 | 1994 |
| HQ | Poznan, Poland | Milan, Italy |
| Team size | 201–500 | 1000+ |
| Rating | 4.3 / 5 | 3.7 / 5 |
| Best for | Companies needing ML development paired with deep, large-scale Python software engineering capacity | Large enterprises wanting ML-driven analytics embedded within a broader business performance management programme |
| Pricing model | Dedicated team, staff augmentation, fixed project | Retainer, dedicated team, fixed project |
| Min. engagement | $25K | $50K |
| Primary tech stack | Python, Django, FastAPI | Python, Power BI, Tableau |
| Industries served | SaaS, Fintech, Healthcare, E-commerce, Enterprise | Enterprise, Financial Services, Retail, Telecommunications |
STX Next vs SDG Group: 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.
SDG Group
SDG Group, founded in 1994 and headquartered in Milan, Italy, is a global management consulting firm with roughly 2,000 employees and offices spanning Milan, Barcelona, London, and beyond. SDG Group specializes in business performance management and analytical applications, with machine learning and AI delivered as part of its broader business intelligence and enterprise analytics consulting practice.
Services and capabilities: STX Next vs SDG Group
| Capability | STX Next | SDG Group |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✓ | ✗ |
Tech stack comparison: STX Next vs SDG Group
| Framework / platform | STX Next | SDG Group |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: STX Next vs SDG Group
| Criterion | STX Next | SDG Group |
|---|---|---|
| Minimum engagement | $25K | $50K |
| Engagement models | Dedicated team, Staff augmentation, Fixed project | Retainer, Dedicated team, Fixed project |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: STX Next vs SDG Group
| Dimension | STX Next | SDG Group |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, Healthcare | Enterprise, Financial Services, Retail |
| Best use cases | ML feature development inside a larger Python software platform, Scaling an engineering team with dedicated Python and ML staff | Enterprise business performance management with an ML component, Large-scale analytical applications for finance or retail clients |
| Typical project type | Dedicated team | Retainer |
STX Next vs SDG Group: 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 |
| SDG Group | |
|---|---|
| + | Three decades of operating history since founding in 1994, as a global management consulting firm |
| + | Enterprise-scale delivery capacity of roughly 2,000 staff across multiple European and international offices |
| + | Deep business performance management heritage grounds AI work in measurable business outcomes |
| + | Established relationships with large enterprise clients across multiple industries |
| - | AI and ML is embedded within a much broader business intelligence and management consulting practice, not a dedicated specialization |
| - | High minimum engagement size, inaccessible for startups or small businesses |
| - | Management-consulting-led engagement model may add overhead versus lean engineering-only ML shops |
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 SDG Group?
SDG Group is the right choice for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme.
Three decades of management consulting heritage applied to enterprise-scale analytics and AI programmes. Minimum engagement starts at $50K. Works best with clients in Enterprise, Financial Services, Retail, Telecommunications.
Decision matrix: STX Next vs SDG Group
| 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 SDG Group
| Use case | STX Next fit | SDG Group 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 business performance management with an ML component | Strong | Strong | Both equally |
| Large-scale analytical applications for finance or retail clients | Limited | Strong | SDG Group |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Strong | Limited | STX Next |
Verdict: STX Next vs SDG Group
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.
SDG Group (3.7/5) is the better choice when large enterprises wanting ML-driven analytics embedded within a broader business performance management programme. If your situation matches those criteria, SDG Group is a competitive option.
Related comparisons
STX Next vs SDG Group FAQ
Is STX Next better than SDG Group?
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. SDG Group is better for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme.
How do STX Next and SDG Group differ in pricing?
STX Next uses dedicated team, staff augmentation, fixed project pricing with a minimum engagement of $25K. SDG Group uses retainer, dedicated team, fixed project pricing with a minimum engagement of $50K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: STX Next or SDG Group?
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 company before shortlisting.
What are the main differences between STX Next and SDG Group?
STX Next's primary differentiator is: one of europe's largest dedicated python engineering companies, with ml and data practices built on that scale. SDG Group's primary differentiator is: three decades of management consulting heritage applied to enterprise-scale analytics and ai programmes. They also differ in team size (201–500 vs 1000+), minimum engagement ($25K vs $50K), and primary industries served (SaaS, Fintech vs Enterprise, Financial Services).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.