Scopic vs Oxagile: full comparison for 2026
Quick verdict
Scopic (3.8/5) edges ahead of Oxagile (3.8/5) overall. Scopic is the better choice for companies wanting senior ML engineers, distributed, competitive rates. Oxagile is the stronger option for Media, sports, AdTech, video and content-analytics ML. The right choice depends on your project size, budget, and required tech stack.
Scopic vs Oxagile: head-to-head summary
| Criterion | Scopic | Oxagile |
|---|---|---|
| Founded | 2006 | 2005 |
| HQ | Marlborough, MA, USA (distributed) | New York, NY, USA / Minsk, Belarus |
| Team size | 1,000–2,000 | 400–600 |
| Rating | 3.8 / 5 | 3.8 / 5 |
| Primary differentiator | 20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk | 20-year video technology specialist with strong computer vision and video analytics ML capability for media, sports, and AdTech clients |
| Pricing model | Dedicated team, T&M, fixed project | Fixed project, dedicated team, T&M |
| Min. engagement | $30K | $25K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, OpenCV |
| Industries served | Healthcare, Manufacturing, Fintech, Logistics, SaaS | E-commerce, Healthcare, Manufacturing, Logistics, SaaS |
Scopic vs Oxagile: overview
Scopic
Scopic is a globally distributed software development company headquartered in Marlborough, Massachusetts, with a remote-first team of 1,000+ engineers spanning 50+ countries. Founded in 2006, Scopic builds custom ML systems using TensorFlow, neural networks, and PyTorch for clients in transportation, healthcare, manufacturing, and finance. The distributed model keeps overhead low while providing senior engineering talent across multiple time zones. Scopic has published ML case studies in medical imaging, predictive maintenance, and financial risk modelling.
Oxagile
Oxagile is a custom software development firm founded in 2005 with offices in New York and Minsk, Belarus, specialising in video domain AI, AdTech, business intelligence, and educational technology. The firm's machine learning practice focuses on object recognition, video analytics, and AI-powered media solutions, drawing on over 20 years of video technology delivery. Oxagile's ML engineering team works with clients in sports, media, advertising, and education to deliver production-grade AI features integrated into video platforms. The firm employs 400+ engineers.
Services and capabilities: Scopic vs Oxagile
| Capability | Scopic | Oxagile |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✓ | ✓ |
| NLP & text analytics | ✗ | ✓ |
| MLOps & deployment | ✗ | ✗ |
| Generative AI | ✗ | ✗ |
| ML consulting & strategy | ✗ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Scopic vs Oxagile
| Framework / platform | Scopic | Oxagile |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | ✓ |
| Scikit-learn | ✓ | N/A |
| AWS SageMaker | N/A | N/A |
| MLflow | N/A | N/A |
| Hugging Face | N/A | N/A |
| LangChain | N/A | N/A |
| Docker/Kubernetes | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: Scopic vs Oxagile
| Criterion | Scopic | Oxagile |
|---|---|---|
| Minimum engagement | $30K | $25K |
| Engagement models | Dedicated team, Time & materials, Fixed project | Fixed project, Dedicated team, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Scopic vs Oxagile
| Dimension | Scopic | Oxagile |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Healthcare, Manufacturing, Fintech | E-commerce, Healthcare, Manufacturing |
| Best use cases | Medical imaging analysis using CNN-based deep learning models, Predictive maintenance systems for manufacturing equipment | Object recognition systems for sports highlight clip generation, Video analytics for media consumption behaviour and content performance |
| Typical project type | Dedicated team | Fixed project |
Scopic vs Oxagile: pros and cons
| Scopic | |
|---|---|
| + | 20-year track record with 1,000+ distributed engineers provides delivery confidence |
| + | Published ML case studies in healthcare imaging, manufacturing maintenance, and financial risk |
| + | Remote-first model provides access to senior talent at competitive rates |
| + | Wide range of ML use cases covered across multiple industries |
| + | Flexible engagement: dedicated team, T&M, or fixed project scope |
| - | Fully distributed model requires strong async communication discipline from client teams |
| - | ML is one of several practice areas — not a pure-play AI specialist firm |
| - | Less emphasis on cutting-edge deep learning research than boutique ML-only firms |
| Oxagile | |
|---|---|
| + | 20+ years of video technology expertise — stronger than most for video-domain ML use cases |
| + | Strong computer vision and object recognition delivery across named media and sports clients |
| + | 400+ engineers provide staffing capacity for medium-to-large concurrent projects |
| + | US-based New York presence for North American client engagement in business hours |
| + | Documented AdTech ML applications including ad relevance and fraud detection models |
| - | Primary strength is video and media ML — less suited to non-video ML use cases |
| - | Belarus-based delivery requires business continuity planning for long-term engagements |
| - | Less documented coverage of modern LLM and generative AI than newer competitors |
Who should choose Scopic?
A typical fit: medical imaging analysis using CNN-based deep learning models.
20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk. Minimum engagement starts at $30K. Works best with clients in Healthcare, Manufacturing, Fintech, Logistics, SaaS.
Who should choose Oxagile?
A typical fit: object recognition systems for sports highlight clip generation.
20-year video technology specialist with strong computer vision and video analytics ML capability for media, sports, and AdTech clients. Minimum engagement starts at $25K. Works best with clients in E-commerce, Healthcare, Manufacturing, Logistics, SaaS.
Decision matrix: Scopic vs Oxagile
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Scopic |
| You need a large dedicated team for an ongoing programme | Scopic |
| Your budget is at the lower end | Oxagile |
| You need specialist depth in a specific vertical | Scopic |
| 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: Scopic vs Oxagile
| Use case | Scopic fit | Oxagile fit | Winner |
|---|---|---|---|
| Medical imaging analysis using CNN-based deep learning models | Strong | Limited | Scopic |
| Predictive maintenance systems for manufacturing equipment | Strong | Limited | Scopic |
| Object recognition systems for sports highlight clip generation | Limited | Strong | Oxagile |
| Video analytics for media consumption behaviour and content performance | Limited | Strong | Oxagile |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Scopic vs Oxagile
Scopic (3.8/5) is the stronger overall choice for most Machine Learning Development projects. 20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk.
Oxagile (3.8/5) is worth a look if you need video analytics for media consumption behaviour and content performance. If your situation matches that, Oxagile is a competitive option.
Related comparisons
Scopic vs Oxagile FAQ
Is Scopic better than Oxagile?
Scopic (3.8/5) scores higher overall, but "better" depends on your use case. Scopic's strongest advantage: 20-year track record with 1,000+ distributed engineers provides delivery confidence. Oxagile's strongest advantage: 20+ years of video technology expertise — stronger than most for video-domain ML use cases.
How do Scopic and Oxagile differ in pricing?
Scopic uses dedicated team, t&m, fixed project pricing with a minimum engagement of $30K. Oxagile uses fixed project, dedicated team, t&m pricing with a minimum engagement of $25K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Scopic or Oxagile?
Scopic 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 Scopic and Oxagile?
Scopic's primary differentiator is: 20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk. Oxagile's primary differentiator is: 20-year video technology specialist with strong computer vision and video analytics ML capability for media, sports, and AdTech clients. They also differ in team size (1,000–2,000 vs 400–600), minimum engagement ($30K vs $25K), and primary industries served (Healthcare, Manufacturing vs E-commerce, Healthcare).