Fractal Analytics vs Oxagile: full comparison for 2026
Last updated: July 2026
Quick verdict
Fractal Analytics (3.9/5) edges ahead of Oxagile (3.8/5) overall. Fractal Analytics is the better choice for fortune 500 companies in consumer packaged goods, retail, and insurance needing enterprise-scale AI and analytics programmes. Oxagile is the stronger option for media, sports, and AdTech companies needing AI and ML capabilities integrated into video platforms and content analytics systems. The right choice depends on your project size, budget, and required tech stack.
Fractal Analytics vs Oxagile: head-to-head summary
| Criterion | Fractal Analytics | Oxagile |
|---|---|---|
| Founded | 2000 | 2005 |
| HQ | Mumbai, India / New York, NY, USA | New York, NY, USA / Minsk, Belarus |
| Team size | 4,000+ | 400–600 |
| Rating | 3.9 / 5 | 3.8 / 5 |
| Best for | Fortune 500 companies in consumer packaged goods, retail, and insurance needing enterprise-scale AI and analytics programmes | Media, sports, and AdTech companies needing AI and ML capabilities integrated into video platforms and content analytics systems |
| Pricing model | Dedicated team, T&M, retainer | Fixed project, dedicated team, T&M |
| Min. engagement | $200K+ | $25K |
| Primary tech stack | Python, Spark, Databricks | Python, TensorFlow, OpenCV |
| Industries served | Fintech, Healthcare, Retail, E-commerce, Manufacturing | E-commerce, Healthcare, Manufacturing, Logistics, SaaS |
Fractal Analytics vs Oxagile: overview
Fractal Analytics
Fractal Analytics is a global AI and analytics company founded in 2000, headquartered in Mumbai, India with significant operations in New York, USA and London, UK, employing 4,000+ professionals. The firm specialises in enterprise AI, advanced analytics, and machine learning for Fortune 500 clients across consumer packaged goods, retail, insurance, and healthcare. Fractal's AI practice covers model development, data engineering, and decision intelligence platforms, with a track record of large-scale analytics programmes at named multinational clients. The company has expanded into generative AI alongside its established analytics and ML practice.
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: Fractal Analytics vs Oxagile
| Capability | Fractal Analytics | Oxagile |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✗ | ✓ |
| NLP & text analytics | ✗ | ✓ |
| MLOps & deployment | ✗ | ✗ |
| Generative AI | ✓ | ✗ |
| ML consulting & strategy | ✓ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Fractal Analytics vs Oxagile
| Framework / platform | Fractal Analytics | Oxagile |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | ✓ |
| Scikit-learn | N/A | N/A |
| AWS SageMaker | ✓ | 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 |
Pricing comparison: Fractal Analytics vs Oxagile
| Criterion | Fractal Analytics | Oxagile |
|---|---|---|
| Minimum engagement | $200K+ | $25K |
| Engagement models | Dedicated team, Time & materials, Consulting retainer | Fixed project, Dedicated team, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Fractal Analytics vs Oxagile
| Dimension | Fractal Analytics | Oxagile |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Healthcare, Retail | E-commerce, Healthcare, Manufacturing |
| Best use cases | Enterprise demand forecasting for global consumer goods manufacturers, Insurance risk scoring and pricing ML at Fortune 500 scale | Object recognition systems for sports highlight clip generation, Video analytics for media consumption behaviour and content performance |
| Typical project type | Dedicated team | Fixed project |
Fractal Analytics vs Oxagile: pros and cons
| Fractal Analytics | |
|---|---|
| + | 25-year track record with named Fortune 500 clients in CPG, retail, and insurance analytics |
| + | 4,000+ professionals with deep enterprise analytics programme delivery experience |
| + | Strong data engineering and decision intelligence capability alongside ML model development |
| + | Generative AI services added to established analytics and ML practice |
| + | US and UK offices for enterprise client relationship management in key markets |
| - | Very high minimum engagement ($200K+) limits access to enterprise-only budgets |
| - | Primary strength is analytics for CPG and retail — less suited to startup ML or deep learning research |
| - | Proprietary analytics platform elements may create vendor lock-in for long-term clients |
| 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 Fractal Analytics?
Fractal Analytics is the right choice for fortune 500 companies in consumer packaged goods, retail, and insurance needing enterprise-scale AI and analytics programmes.
25-year enterprise AI firm with documented Fortune 500 programmes in CPG, retail, and insurance analytics across 4,000+ professionals. Minimum engagement starts at $200K+. Works best with clients in Fintech, Healthcare, Retail, E-commerce, Manufacturing.
Who should choose Oxagile?
Oxagile is the right choice for media, sports, and AdTech companies needing AI and ML capabilities integrated into video platforms and content analytics systems.
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: Fractal Analytics vs Oxagile
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Oxagile |
| You need a large dedicated team for an ongoing programme | Fractal Analytics |
| Your budget is at the lower end | Oxagile |
| You need specialist depth in a specific vertical | Fractal Analytics |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Fractal Analytics |
Use case fit: Fractal Analytics vs Oxagile
| Use case | Fractal Analytics fit | Oxagile fit | Winner |
|---|---|---|---|
| Enterprise demand forecasting for global consumer goods manufacturers | Strong | Limited | Fractal Analytics |
| Insurance risk scoring and pricing ML at Fortune 500 scale | Strong | Limited | Fractal Analytics |
| 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: Fractal Analytics vs Oxagile
Fractal Analytics (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 25-year enterprise AI firm with documented Fortune 500 programmes in CPG, retail, and insurance analytics across 4,000+ professionals. It is best for fortune 500 companies in consumer packaged goods, retail, and insurance needing enterprise-scale AI and analytics programmes.
Oxagile (3.8/5) is the better choice when media, sports, and AdTech companies needing AI and ML capabilities integrated into video platforms and content analytics systems. If your situation matches those criteria, Oxagile is a competitive option.
Related comparisons
Fractal Analytics vs Oxagile FAQ
Is Fractal Analytics better than Oxagile?
Fractal Analytics (3.9/5) scores higher overall, but "better" depends on your use case. Fractal Analytics is better for fortune 500 companies in consumer packaged goods, retail, and insurance needing enterprise-scale AI and analytics programmes. Oxagile is better for media, sports, and AdTech companies needing AI and ML capabilities integrated into video platforms and content analytics systems.
How do Fractal Analytics and Oxagile differ in pricing?
Fractal Analytics uses dedicated team, t&m, retainer pricing with a minimum engagement of $200K+. 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: Fractal Analytics 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 Fractal Analytics and Oxagile?
Fractal Analytics's primary differentiator is: 25-year enterprise ai firm with documented fortune 500 programmes in cpg, retail, and insurance analytics across 4,000+ professionals. 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 (4,000+ vs 400–600), minimum engagement ($200K+ vs $25K), and primary industries served (Fintech, Healthcare vs E-commerce, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.