Codiste vs Oxagile: full comparison for 2026
Last updated: July 2026
Quick verdict
Codiste (4.3/5) edges ahead of Oxagile (3.8/5) overall. Codiste is the better choice for startups and mid-market companies needing full ML lifecycle delivery from data engineering through to a deployed production system. 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.
Codiste vs Oxagile: head-to-head summary
| Criterion | Codiste | Oxagile |
|---|---|---|
| Founded | 2016 | 2005 |
| HQ | Mumbai, India / New York, NY, USA | New York, NY, USA / Minsk, Belarus |
| Team size | 200–500 | 400–600 |
| Rating | 4.3 / 5 | 3.8 / 5 |
| Best for | Startups and mid-market companies needing full ML lifecycle delivery from data engineering through to a deployed production system | Media, sports, and AdTech companies needing AI and ML capabilities integrated into video platforms and content analytics systems |
| Pricing model | Fixed project, dedicated team | Fixed project, dedicated team, T&M |
| Min. engagement | $25K | $25K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, OpenCV |
| Industries served | SaaS, E-commerce, Healthcare, Fintech, Retail | E-commerce, Healthcare, Manufacturing, Logistics, SaaS |
Codiste vs Oxagile: overview
Codiste
Codiste is an AI-first software engineering company with offices in India and the United States, specialising in custom machine learning development, generative AI systems, and MLOps infrastructure. The firm covers the full ML lifecycle including data engineering, model development, integration, and post-deployment monitoring. Codiste's engineering practice draws on Python, TensorFlow, PyTorch, and LangChain, with delivery through dedicated teams and fixed-price project structures. The company positions itself as a delivery-focused ML firm with an emphasis on taking models beyond prototype into production operation (per company website; independently unverifiable).
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: Codiste vs Oxagile
| Capability | Codiste | Oxagile |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✗ | ✓ |
| NLP & text analytics | ✗ | ✓ |
| MLOps & deployment | ✓ | ✗ |
| Generative AI | ✓ | ✗ |
| ML consulting & strategy | ✗ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Codiste vs Oxagile
| Framework / platform | Codiste | Oxagile |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | ✓ |
| Scikit-learn | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| MLflow | ✓ | N/A |
| Hugging Face | N/A | N/A |
| LangChain | ✓ | N/A |
| Docker/Kubernetes | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: Codiste vs Oxagile
| Criterion | Codiste | Oxagile |
|---|---|---|
| Minimum engagement | $25K | $25K |
| 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: Codiste vs Oxagile
| Dimension | Codiste | Oxagile |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, E-commerce, Healthcare | E-commerce, Healthcare, Manufacturing |
| Best use cases | MLOps pipeline setup and infrastructure for data science teams going to production, Generative AI chatbots and content automation tools for SaaS products | Object recognition systems for sports highlight clip generation, Video analytics for media consumption behaviour and content performance |
| Typical project type | Fixed project | Fixed project |
Codiste vs Oxagile: pros and cons
| Codiste | |
|---|---|
| + | AI-first positioning means ML delivery is the core business, not a side practice |
| + | Strong MLOps coverage for production deployment, monitoring, and model management |
| + | Generative AI capability alongside classical ML development in a single team |
| + | Flexible engagement: fixed project or dedicated team models available |
| + | $25K minimum accessible for mid-market project initiations |
| - | Founded relatively recently; shorter independently verifiable track record than older firms |
| - | No widely cited independent review platform rating to validate delivery quality claims |
| - | India-primary delivery requires proactive timezone coordination for US and EU 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 Codiste?
Codiste is the right choice for startups and mid-market companies needing full ML lifecycle delivery from data engineering through to a deployed production system.
AI-first engineering firm with explicit MLOps focus and generative AI capability alongside classical ML model development. Minimum engagement starts at $25K. Works best with clients in SaaS, E-commerce, Healthcare, Fintech, Retail.
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: Codiste vs Oxagile
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Codiste |
| You need a large dedicated team for an ongoing programme | Codiste |
| Your budget is at the lower end | Codiste |
| You need specialist depth in a specific vertical | Codiste |
| 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: Codiste vs Oxagile
| Use case | Codiste fit | Oxagile fit | Winner |
|---|---|---|---|
| MLOps pipeline setup and infrastructure for data science teams going to production | Strong | Limited | Codiste |
| Generative AI chatbots and content automation tools for SaaS products | Strong | Limited | Codiste |
| 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: Codiste vs Oxagile
Codiste (4.3/5) is the stronger overall choice for most Machine Learning Development projects. AI-first engineering firm with explicit MLOps focus and generative AI capability alongside classical ML model development. It is best for startups and mid-market companies needing full ML lifecycle delivery from data engineering through to a deployed production system.
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
Codiste vs Oxagile FAQ
Is Codiste better than Oxagile?
Codiste (4.3/5) scores higher overall, but "better" depends on your use case. Codiste is better for startups and mid-market companies needing full ML lifecycle delivery from data engineering through to a deployed production system. Oxagile is better for media, sports, and AdTech companies needing AI and ML capabilities integrated into video platforms and content analytics systems.
How do Codiste and Oxagile differ in pricing?
Codiste uses fixed project, dedicated team pricing with a minimum engagement of $25K. 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: Codiste 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 Codiste and Oxagile?
Codiste's primary differentiator is: ai-first engineering firm with explicit mlops focus and generative ai capability alongside classical ml model development. 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 (200–500 vs 400–600), minimum engagement ($25K vs $25K), and primary industries served (SaaS, E-commerce vs E-commerce, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.