MobiDev vs STX Next: full comparison for 2026
Last updated: July 2026
Quick verdict
MobiDev (4.1/5) edges ahead of STX Next (4.0/5) overall. MobiDev is the better choice for companies needing ML development integrated with mobile or web product engineering from a US/UK-managed team with European R&D. STX Next is the stronger option for python-first companies needing ML capability embedded within software products rather than standalone AI systems. The right choice depends on your project size, budget, and required tech stack.
MobiDev vs STX Next: head-to-head summary
| Criterion | MobiDev | STX Next |
|---|---|---|
| Founded | 2009 | 2005 |
| HQ | Atlanta, GA, USA / Sheffield, UK | Poznań, Poland |
| Team size | 400–600 | 700–1,000 |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Best for | Companies needing ML development integrated with mobile or web product engineering from a US/UK-managed team with European R&D | Python-first companies needing ML capability embedded within software products rather than standalone AI systems |
| Pricing model | Fixed project, dedicated team, T&M | Fixed project, dedicated team, T&M |
| Min. engagement | $30K | $50K |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Django, FastAPI |
| Industries served | Healthcare, Fintech, Retail, Logistics, E-commerce | Fintech, Healthcare, SaaS, E-commerce, Manufacturing |
MobiDev vs STX Next: overview
MobiDev
MobiDev is a software and machine learning company headquartered in Atlanta, Georgia and Sheffield, UK, with R&D centers in Lodz, Poland and Chernivtsi, Ukraine. The firm employs 400+ engineers and offers full-range machine learning services including deep learning, data science, computer vision, NLP, and GPT model integration. MobiDev's ML practice covers all stages from data collection and model training through integration and post-deployment monitoring. The company serves clients across healthcare, fintech, retail, and logistics with a product-engineering mindset that emphasises buildable, maintainable production systems.
STX Next
STX Next is a software development company founded in 2005 and headquartered in Poznań, Poland, operating as Europe's largest Python software house with 700+ engineers. The firm's machine learning practice focuses on operationalising ML models within complete software products rather than delivering standalone ML components, reflecting its software engineering heritage. STX Next serves clients across fintech, SaaS, healthcare, and e-commerce with Python-native ML development, model integration, and MLOps infrastructure. The company has 20 years of software delivery history across European and US client bases.
Services and capabilities: MobiDev vs STX Next
| Capability | MobiDev | STX Next |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP & text analytics | ✓ | ✓ |
| MLOps & deployment | ✓ | ✓ |
| Generative AI | ✓ | ✗ |
| ML consulting & strategy | ✗ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: MobiDev vs STX Next
| Framework / platform | MobiDev | STX Next |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| Scikit-learn | N/A | ✓ |
| AWS SageMaker | N/A | N/A |
| MLflow | N/A | ✓ |
| Hugging Face | ✓ | N/A |
| LangChain | ✓ | N/A |
| Docker/Kubernetes | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: MobiDev vs STX Next
| Criterion | MobiDev | STX Next |
|---|---|---|
| Minimum engagement | $30K | $50K |
| Engagement models | Fixed project, Dedicated team, Time & materials | Fixed project, Dedicated team, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: MobiDev vs STX Next
| Dimension | MobiDev | STX Next |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Healthcare, Fintech, Retail | Fintech, Healthcare, SaaS |
| Best use cases | ML features integrated into mobile and web product builds for healthcare and fintech, Deep learning models for medical imaging analysis and diagnostics | Python-native ML features built into web applications for fintech and healthcare, MLOps pipeline construction for data science teams going to production |
| Typical project type | Fixed project | Fixed project |
MobiDev vs STX Next: pros and cons
| MobiDev | |
|---|---|
| + | US and UK presence with European R&D centres for cost-efficient delivery without quality compromise |
| + | Full-range ML coverage including deep learning, NLP, computer vision, and generative AI |
| + | 400+ engineers provide staffing capacity for scaling concurrent programmes |
| + | Product engineering mindset ensures ML is built into working software, not isolated prototypes |
| + | Strong GPT and LLM integration capability for modern AI-powered product features |
| - | Broad ML coverage may lack specialist depth on highly novel deep learning research problems |
| - | Poland and Ukraine R&D centres require business continuity planning for critical long-term programmes |
| - | Case study library is less publicly extensive than some larger or boutique competitors |
| STX Next | |
|---|---|
| + | Europe's largest Python engineering firm with deep Python-native ML expertise |
| + | 700+ engineers give strong staffing depth for scaling concurrent programmes |
| + | 20-year track record provides risk comfort for long-term technology partnerships |
| + | ML integrated within software products reduces prototype-to-production handoff friction |
| + | Strong European market coverage with US and UK clients also served |
| - | ML is one practice within a broader software development business rather than a primary specialisation |
| - | Less focus on standalone AI/ML systems — best where ML is embedded in Python products |
| - | $50K minimum may price out very early-stage ML exploration or PoC projects |
Who should choose MobiDev?
MobiDev is the right choice for companies needing ML development integrated with mobile or web product engineering from a US/UK-managed team with European R&D.
US/UK-managed ML engineering firm with 400+ engineers and documented deep learning, NLP, and GPT integration across product development. Minimum engagement starts at $30K. Works best with clients in Healthcare, Fintech, Retail, Logistics, E-commerce.
Who should choose STX Next?
STX Next is the right choice for python-first companies needing ML capability embedded within software products rather than standalone AI systems.
Europe's largest Python engineering firm with 700+ engineers, making ML a natural extension of existing Python product development. Minimum engagement starts at $50K. Works best with clients in Fintech, Healthcare, SaaS, E-commerce, Manufacturing.
Decision matrix: MobiDev vs STX Next
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | MobiDev |
| You need a large dedicated team for an ongoing programme | MobiDev |
| Your budget is at the lower end | MobiDev |
| You need specialist depth in a specific vertical | MobiDev |
| 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: MobiDev vs STX Next
| Use case | MobiDev fit | STX Next fit | Winner |
|---|---|---|---|
| ML features integrated into mobile and web product builds for healthcare and fintech | Strong | Strong | Both equally |
| Deep learning models for medical imaging analysis and diagnostics | Strong | Limited | MobiDev |
| Python-native ML features built into web applications for fintech and healthcare | Limited | Strong | STX Next |
| MLOps pipeline construction for data science teams going to production | Limited | Strong | STX Next |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: MobiDev vs STX Next
MobiDev (4.1/5) is the stronger overall choice for most Machine Learning Development projects. US/UK-managed ML engineering firm with 400+ engineers and documented deep learning, NLP, and GPT integration across product development. It is best for companies needing ML development integrated with mobile or web product engineering from a US/UK-managed team with European R&D.
STX Next (4.0/5) is the better choice when python-first companies needing ML capability embedded within software products rather than standalone AI systems. If your situation matches those criteria, STX Next is a competitive option.
Related comparisons
MobiDev vs STX Next FAQ
Is MobiDev better than STX Next?
MobiDev (4.1/5) scores higher overall, but "better" depends on your use case. MobiDev is better for companies needing ML development integrated with mobile or web product engineering from a US/UK-managed team with European R&D. STX Next is better for python-first companies needing ML capability embedded within software products rather than standalone AI systems.
How do MobiDev and STX Next differ in pricing?
MobiDev uses fixed project, dedicated team, t&m pricing with a minimum engagement of $30K. STX Next uses fixed project, dedicated team, t&m 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: MobiDev or STX Next?
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 MobiDev and STX Next?
MobiDev's primary differentiator is: us/uk-managed ml engineering firm with 400+ engineers and documented deep learning, nlp, and gpt integration across product development. STX Next's primary differentiator is: europe's largest python engineering firm with 700+ engineers, making ml a natural extension of existing python product development. They also differ in team size (400–600 vs 700–1,000), minimum engagement ($30K vs $50K), and primary industries served (Healthcare, Fintech vs Fintech, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.