Scopic vs Oxagile: full comparison for 2026
Last updated: July 2026
Quick verdict
Scopic (3.9/5) edges ahead of Oxagile (3.8/5) overall. Scopic is the better choice for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability. Oxagile is the stronger option for media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise. 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 | New York, NY, USA |
| Team size | 250–500 | 250–500 |
| Rating | 3.9 / 5 | 3.8 / 5 |
| Best for | Organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability | Media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise |
| Pricing model | Fixed project, T&M, Dedicated team | Fixed project, T&M, Dedicated team |
| Min. engagement | $20K | $25K |
| Primary tech stack | TensorFlow, PyTorch, Keras | TensorFlow, PyTorch, OpenCV |
| Industries served | transportation, healthcare, manufacturing, financial services, edtech | media, advertising, retail, sports, healthcare |
Scopic vs Oxagile: overview
Scopic
Scopic is a globally distributed software development company founded in 2006 and headquartered in Marlborough, Massachusetts. The company employs 250–500 professionals and has 20 years of experience building custom ML systems using TensorFlow, neural networks, PyTorch, and computer vision pipelines. Scopic has confirmed production ML deployments across transportation, healthcare, manufacturing, and financial services.
Oxagile
Oxagile is a custom software development vendor founded in 2005 and headquartered in New York, with delivery centers in Eastern Europe. The company has 20+ years of video domain expertise and has applied machine learning to video understanding, visual search, and real-time video analytics for clients in media, advertising, sports, and retail. Oxagile's ML practice is particularly strong in use cases where video processing is the core data source.
Services and capabilities: Scopic vs Oxagile
| Capability | Scopic | Oxagile |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| ML consulting | ✗ | ✓ |
| Deep learning | ✓ | ✓ |
| NLP | ✓ | ✗ |
| Computer vision | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Predictive analytics | ✓ | ✗ |
| Generative AI | ✗ | ✗ |
| Data engineering | ✗ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: Scopic vs Oxagile
| Framework / platform | Scopic | Oxagile |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| Scikit-Learn | ✓ | N/A |
| LangChain | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
| GCP Vertex AI | N/A | N/A |
| Kubernetes | N/A | ✓ |
| Apache Spark | N/A | N/A |
| MLflow | N/A | N/A |
Pricing comparison: Scopic vs Oxagile
| Criterion | Scopic | Oxagile |
|---|---|---|
| Minimum engagement | $20K | $25K |
| Engagement models | Fixed project, T&M, Dedicated team | Fixed project, T&M, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Scopic vs Oxagile
| Dimension | Scopic | Oxagile |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | transportation, healthcare, manufacturing | media, advertising, retail |
| Best use cases | Custom computer vision pipeline development for transportation safety or logistics automation, Deep learning model development for medical image analysis or clinical data classification | Video content analysis ML for content moderation, tagging, or recommendation, Computer vision model development for sports performance analysis |
| Typical project type | Fixed project | Fixed project |
Scopic vs Oxagile: pros and cons
| Scopic | |
|---|---|
| + | 20 years of distributed ML delivery with consistent process maturity across time zones |
| + | Deep computer vision and neural network expertise with production deployments in transportation |
| + | Custom ML system engineering — not platform-reliant solutions dependent on third-party services |
| + | Accessible minimum engagement and competitive rates for the level of specialization offered |
| + | Healthcare ML experience with sensitivity to data privacy and regulatory considerations |
| - | Distributed-first model may introduce coordination overhead for clients preferring on-site collaboration |
| - | Less public brand presence than US-headquartered firms of similar capability |
| - | Less generative AI and LLM tooling depth than newer AI-first firms |
| Oxagile | |
|---|---|
| + | 20+ years of video technology expertise is a genuinely rare differentiator in the ML market |
| + | NVIDIA CUDA expertise for GPU-accelerated video ML inference at production scale |
| + | AdTech ML specialization for audience targeting and real-time bidding optimization models |
| + | WebRTC and live video stream processing capability alongside batch video analysis |
| + | Eastern European delivery with New York client-facing presence |
| - | Video-first specialization means less breadth for non-video ML use cases |
| - | Less generative AI LLM tooling depth compared to AI-first firms |
| - | Limited public case studies outside media, AdTech, and sports verticals |
Who should choose Scopic?
Scopic is the right choice for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability.
20+ years as a distributed software company gives Scopic strong custom ML engineering discipline with confirmed production deployments across transportation and healthcare. Minimum engagement starts at $20K. Works best with clients in transportation, healthcare, manufacturing, financial services, edtech.
Who should choose Oxagile?
Oxagile is the right choice for media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise.
20+ years of video domain expertise uniquely positions Oxagile for ML use cases involving video understanding, visual search, and real-time video analytics. Minimum engagement starts at $25K. Works best with clients in media, advertising, retail, sports, healthcare.
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 | Scopic |
| 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 | Oxagile |
Use case fit: Scopic vs Oxagile
| Use case | Scopic fit | Oxagile fit | Winner |
|---|---|---|---|
| Custom computer vision pipeline development for transportation safety or logistics automation | Strong | Limited | Scopic |
| Deep learning model development for medical image analysis or clinical data classification | Strong | Limited | Scopic |
| Video content analysis ML for content moderation, tagging, or recommendation | Limited | Strong | Oxagile |
| Computer vision model development for sports performance analysis | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Scopic vs Oxagile
Scopic (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 20+ years as a distributed software company gives Scopic strong custom ML engineering discipline with confirmed production deployments across transportation and healthcare. It is best for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability.
Oxagile (3.8/5) is the better choice when media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise. If your situation matches those criteria, Oxagile is a competitive option.
Related comparisons
Scopic vs Oxagile FAQ
Is Scopic better than Oxagile?
Scopic (3.9/5) scores higher overall, but "better" depends on your use case. Scopic is better for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability. Oxagile is better for media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise.
How do Scopic and Oxagile differ in pricing?
Scopic uses fixed project, t&m, dedicated team pricing with a minimum engagement of $20K. Oxagile uses fixed project, t&m, dedicated team 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+ years as a distributed software company gives scopic strong custom ml engineering discipline with confirmed production deployments across transportation and healthcare. Oxagile's primary differentiator is: 20+ years of video domain expertise uniquely positions oxagile for ml use cases involving video understanding, visual search, and real-time video analytics. They also differ in team size (250–500 vs 250–500), minimum engagement ($20K vs $25K), and primary industries served (transportation, healthcare vs media, advertising).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.