STX Next vs Oxagile: full comparison for 2026
Last updated: July 2026
Quick verdict
STX Next (4.3/5) edges ahead of Oxagile (4.2/5) overall. STX Next is the better choice for python-stack product companies that need ML tightly integrated into an existing software system with MLOps from day one. Oxagile is the stronger option for enterprises in healthcare, media, or retail seeking cost-effective ML development with Eastern European engineering quality. The right choice depends on your project size, budget, and required tech stack.
STX Next vs Oxagile: head-to-head summary
| Criterion | STX Next | Oxagile |
|---|---|---|
| Founded | 2005 | 2005 |
| HQ | Wrocław, Poland | Minsk, Belarus |
| Team size | 600+ | 250–999 |
| Rating | 4.3 / 5 | 4.2 / 5 |
| Best for | Python-stack product companies that need ML tightly integrated into an existing software system with MLOps from day one | Enterprises in healthcare, media, or retail seeking cost-effective ML development with Eastern European engineering quality |
| Pricing model | Fixed project, T&M, dedicated team | Fixed project, T&M, dedicated team |
| Min. engagement | $50K | $20K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, OpenCV |
| Industries served | Financial Services, Healthcare & Life Sciences, Media & Entertainment, Logistics & Supply Chain, SaaS & Technology | Healthcare & Life Sciences, Media & Entertainment, Financial Services, Manufacturing & Industrial, Retail & E-commerce |
STX Next vs Oxagile: overview
STX Next
STX Next is one of Europe's largest Python software houses, founded in 2005 and headquartered in Wrocław, Poland, with 600+ engineers. The firm's ML strength lies in operationalising models within complete software systems — engineering the full software ecosystem required for ML to function reliably in production. In 2026, STX Next has increased emphasis on MLOps, deployment automation, and long-term model maintainability, making it a strong choice for teams that need ML embedded in larger Python-based products.
Oxagile
Oxagile is a software and AI development company founded in 2005 and headquartered in Minsk, Belarus, with 250–999 employees. The firm offers AI software development services with a focus on data-driven solutions for digital transformation. Oxagile is recognised for connected care AI in healthcare, computer vision in media and retail, and custom ML systems for enterprise clients across multiple verticals.
Services and capabilities: STX Next vs Oxagile
| Capability | STX Next | Oxagile |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✗ | ✓ |
| NLP & LLMs | ✗ | ✓ |
| MLOps & deployment | ✓ | ✓ |
| Generative AI | ✓ | ✗ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: STX Next vs Oxagile
| Framework / platform | STX Next | Oxagile |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
| Vertex AI | N/A | N/A |
| Scikit-learn | N/A | ✓ |
| Hugging Face | N/A | N/A |
| Apache Spark | N/A | N/A |
| Kubernetes | ✓ | N/A |
| MLflow | ✓ | N/A |
Pricing comparison: STX Next vs Oxagile
| Criterion | STX Next | Oxagile |
|---|---|---|
| Minimum engagement | $50K | $20K |
| Engagement models | Fixed project, Time & materials, Dedicated team | Fixed project, Time & materials, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: STX Next vs Oxagile
| Dimension | STX Next | Oxagile |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial Services, Healthcare & Life Sciences, Media & Entertainment | Healthcare & Life Sciences, Media & Entertainment, Financial Services |
| Best use cases | ML model integrated into an existing Python-based fintech product with MLOps pipeline, MLOps infrastructure build for a media company's recommendation engine | Connected care AI for remote patient monitoring and telemedicine platform, Computer vision content moderation system for media streaming service |
| Typical project type | Fixed project | Fixed project |
STX Next vs Oxagile: pros and cons
| STX Next | |
|---|---|
| + | Europe's largest Python house — unmatched Python talent pool depth for ML-in-Python-stack projects |
| + | MLOps-first philosophy — deployment automation and monitoring built in from project start |
| + | Full software ecosystem delivery: APIs, data pipelines, model serving, and frontend in one team |
| + | Strong EU client base with GDPR-compliant delivery frameworks |
| + | 600+ engineer scale enables large dedicated ML team staffing for multi-year programmes |
| - | $50K minimum excludes smaller ML projects and startups at early stages |
| - | Less hardware AI, edge inference, or embedded ML depth than firms with hardware backgrounds |
| - | Python specialisation means less flexibility for projects requiring Scala, Java, or other ML-adjacent stacks |
| Oxagile | |
|---|---|
| + | Competitive rates — 40–60% lower than US equivalents at comparable engineering quality |
| + | Connected care and healthcare imaging AI track record with PACS integration experience |
| + | Lower $20K minimum makes specialist ML accessible for budget-conscious projects |
| + | Computer vision depth in both media and industrial inspection use cases |
| + | Flexible three-model engagement covers fixed scope through long-term dedicated teams |
| - | Belarus-based delivery carries geopolitical risk and potential regulatory complications for some enterprises |
| - | Less generative AI and LLM depth than firms with more recent AI-native practices |
| - | Brand visibility lower than US-headquartered peers in North American procurement processes |
Who should choose STX Next?
STX Next is the right choice for python-stack product companies that need ML tightly integrated into an existing software system with MLOps from day one.
Europe's largest Python shop — ML is embedded in full-stack Python systems with MLOps, not delivered as an isolated model. Minimum engagement starts at $50K. Works best with clients in Financial Services, Healthcare & Life Sciences, Media & Entertainment, Logistics & Supply Chain, SaaS & Technology.
Who should choose Oxagile?
Oxagile is the right choice for enterprises in healthcare, media, or retail seeking cost-effective ML development with Eastern European engineering quality.
Strong connected-care and healthcare AI track record combined with 40–60% cost advantage versus US equivalents. Minimum engagement starts at $20K. Works best with clients in Healthcare & Life Sciences, Media & Entertainment, Financial Services, Manufacturing & Industrial, Retail & E-commerce.
Decision matrix: STX Next vs Oxagile
| 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 | Oxagile |
| 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 | STX Next |
Use case fit: STX Next vs Oxagile
| Use case | STX Next fit | Oxagile fit | Winner |
|---|---|---|---|
| ML model integrated into an existing Python-based fintech product with MLOps pipeline | Strong | Strong | Both equally |
| MLOps infrastructure build for a media company's recommendation engine | Strong | Limited | STX Next |
| Connected care AI for remote patient monitoring and telemedicine platform | Limited | Strong | Oxagile |
| Computer vision content moderation system for media streaming service | Limited | Strong | Oxagile |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: STX Next vs Oxagile
STX Next (4.3/5) is the stronger overall choice for most Machine Learning Development projects. Europe's largest Python shop — ML is embedded in full-stack Python systems with MLOps, not delivered as an isolated model. It is best for python-stack product companies that need ML tightly integrated into an existing software system with MLOps from day one.
Oxagile (4.2/5) is the better choice when enterprises in healthcare, media, or retail seeking cost-effective ML development with Eastern European engineering quality. If your situation matches those criteria, Oxagile is a competitive option.
Related comparisons
STX Next vs Oxagile FAQ
Is STX Next better than Oxagile?
STX Next (4.3/5) scores higher overall, but "better" depends on your use case. STX Next is better for python-stack product companies that need ML tightly integrated into an existing software system with MLOps from day one. Oxagile is better for enterprises in healthcare, media, or retail seeking cost-effective ML development with Eastern European engineering quality.
How do STX Next and Oxagile differ in pricing?
STX Next uses fixed project, t&m, dedicated team pricing with a minimum engagement of $50K. Oxagile uses fixed project, t&m, dedicated team pricing with a minimum engagement of $20K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: STX Next or Oxagile?
Oxagile 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 Oxagile?
STX Next's primary differentiator is: europe's largest python shop — ml is embedded in full-stack python systems with mlops, not delivered as an isolated model. Oxagile's primary differentiator is: strong connected-care and healthcare ai track record combined with 40–60% cost advantage versus us equivalents. They also differ in team size (600+ vs 250–999), minimum engagement ($50K vs $20K), and primary industries served (Financial Services, Healthcare & Life Sciences vs Healthcare & Life Sciences, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.