Miquido vs Oxagile: full comparison for 2026
Last updated: July 2026
Quick verdict
Miquido (4.0/5) edges ahead of Oxagile (3.8/5) overall. Miquido is the better choice for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise. 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.
Miquido vs Oxagile: head-to-head summary
| Criterion | Miquido | Oxagile |
|---|---|---|
| Founded | 2011 | 2005 |
| HQ | Krakow, Poland | New York, NY, USA |
| Team size | 150–300 | 250–500 |
| Rating | 4.0 / 5 | 3.8 / 5 |
| Best for | Product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise | 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, Dedicated team, T&M | Fixed project, T&M, Dedicated team |
| Min. engagement | $30K | $25K |
| Primary tech stack | TensorFlow, PyTorch, Python | TensorFlow, PyTorch, OpenCV |
| Industries served | fintech, e-commerce, healthcare, entertainment, media | media, advertising, retail, sports, healthcare |
Miquido vs Oxagile: overview
Miquido
Miquido is a Google-certified software development company founded in 2011 and headquartered in Krakow, Poland. The company employs 150–300 professionals and has delivered 250+ digital products for clients including Warner, Dolby, Abbey Road Studios, Skyscanner, and TUI. Miquido's ML practice is distinguished by its integration with product design expertise — delivering machine learning inside well-crafted user experiences rather than as isolated algorithmic components.
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: Miquido vs Oxagile
| Capability | Miquido | Oxagile |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| ML consulting | ✓ | ✓ |
| Deep learning | ✗ | ✓ |
| NLP | ✓ | ✗ |
| Computer vision | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Predictive analytics | ✗ | ✗ |
| Generative AI | ✓ | ✗ |
| Data engineering | ✗ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: Miquido vs Oxagile
| Framework / platform | Miquido | Oxagile |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| Scikit-Learn | N/A | 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: Miquido vs Oxagile
| Criterion | Miquido | Oxagile |
|---|---|---|
| Minimum engagement | $30K | $25K |
| Engagement models | Fixed project, Dedicated team, T&M | Fixed project, T&M, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Miquido vs Oxagile
| Dimension | Miquido | Oxagile |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | fintech, e-commerce, healthcare | media, advertising, retail |
| Best use cases | ML feature integration into mobile and web consumer products (e.g., recommendation, personalization), Computer vision feature development for entertainment or retail apps | 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 |
Miquido vs Oxagile: pros and cons
| Miquido | |
|---|---|
| + | Google-certified partnership confirms cloud ML deployment capability on GCP independently |
| + | Named enterprise clients (Warner, Dolby, Skyscanner, TUI) verify delivery at brand scale |
| + | ML plus product design combination delivers end-user-facing AI features, not back-end-only models |
| + | 9/10 projects from referrals signals strong client satisfaction and delivery consistency |
| + | Krakow base with North American, European, and Middle Eastern client experience |
| - | Hourly rates ($70–$150) are higher than Eastern European average for similar team size |
| - | Product-first focus may mean less depth in complex research-adjacent ML or custom model architectures |
| - | Less visible in the US market compared to North American competitors of equivalent capability |
| 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 Miquido?
Miquido is the right choice for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise.
Google-certified AI/ML capability paired with strong product design — clients receive ML that works inside well-crafted user experiences, not bolted-on algorithms. Minimum engagement starts at $30K. Works best with clients in fintech, e-commerce, healthcare, entertainment, media.
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: Miquido vs Oxagile
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Miquido |
| You need a large dedicated team for an ongoing programme | Miquido |
| Your budget is at the lower end | Oxagile |
| You need specialist depth in a specific vertical | Miquido |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Miquido |
Use case fit: Miquido vs Oxagile
| Use case | Miquido fit | Oxagile fit | Winner |
|---|---|---|---|
| ML feature integration into mobile and web consumer products (e.g., recommendation, personalization) | Strong | Strong | Both equally |
| Computer vision feature development for entertainment or retail apps | Strong | Strong | Both equally |
| 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: Miquido vs Oxagile
Miquido (4.0/5) is the stronger overall choice for most Machine Learning Development projects. Google-certified AI/ML capability paired with strong product design — clients receive ML that works inside well-crafted user experiences, not bolted-on algorithms. It is best for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise.
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
Miquido vs Oxagile FAQ
Is Miquido better than Oxagile?
Miquido (4.0/5) scores higher overall, but "better" depends on your use case. Miquido is better for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise. 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 Miquido and Oxagile differ in pricing?
Miquido uses fixed project, dedicated team, t&m pricing with a minimum engagement of $30K. 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: Miquido 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 Miquido and Oxagile?
Miquido's primary differentiator is: google-certified ai/ml capability paired with strong product design — clients receive ml that works inside well-crafted user experiences, not bolted-on algorithms. 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 (150–300 vs 250–500), minimum engagement ($30K vs $25K), and primary industries served (fintech, e-commerce vs media, advertising).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.