Oxagile vs 10Pearls: full comparison for 2026
Last updated: July 2026
Quick verdict
Oxagile (3.8/5) edges ahead of 10Pearls (3.8/5) overall. Oxagile is the better 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. 10Pearls is the stronger option for uS-based enterprises and government contractors needing AI-native delivery teams with North American proximity, government sector experience, and LATAM delivery capacity. The right choice depends on your project size, budget, and required tech stack.
Oxagile vs 10Pearls: head-to-head summary
| Criterion | Oxagile | 10Pearls |
|---|---|---|
| Founded | 2005 | 2004 |
| HQ | New York, NY, USA | Vienna, VA, USA |
| Team size | 250–500 | 1,400+ |
| Rating | 3.8 / 5 | 3.8 / 5 |
| Best for | Media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise | US-based enterprises and government contractors needing AI-native delivery teams with North American proximity, government sector experience, and LATAM delivery capacity |
| Pricing model | Fixed project, T&M, Dedicated team | Fixed project, Dedicated team, T&M |
| Min. engagement | $25K | $30K |
| Primary tech stack | TensorFlow, PyTorch, OpenCV | Python, TensorFlow, PyTorch |
| Industries served | media, advertising, retail, sports, healthcare | healthcare, financial services, government, retail, logistics |
Oxagile vs 10Pearls: overview
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.
10Pearls
10Pearls is an AI-powered digital engineering company founded in 2004 and headquartered in Vienna, Virginia, in the Washington DC metro area. The company employs 1,400+ experts across North America, Latin America, Europe, and South Asia, and has been recognized four consecutive times on the CRN Solution Provider 500 list for enterprise AI delivery. 10Pearls serves enterprise and government clients in healthcare, financial services, and logistics with a focus on ML, cloud architecture, and cybersecurity-aware AI development.
Services and capabilities: Oxagile vs 10Pearls
| Capability | Oxagile | 10Pearls |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| ML consulting | ✓ | ✓ |
| Deep learning | ✓ | ✗ |
| NLP | ✗ | ✗ |
| Computer vision | ✓ | ✗ |
| MLOps | ✗ | ✗ |
| Predictive analytics | ✗ | ✓ |
| Generative AI | ✗ | ✓ |
| Data engineering | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: Oxagile vs 10Pearls
| Framework / platform | Oxagile | 10Pearls |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| Scikit-Learn | N/A | N/A |
| LangChain | N/A | N/A |
| AWS SageMaker | N/A | ✓ |
| Azure ML | N/A | ✓ |
| GCP Vertex AI | N/A | N/A |
| Kubernetes | ✓ | ✓ |
| Apache Spark | N/A | ✓ |
| MLflow | N/A | N/A |
Pricing comparison: Oxagile vs 10Pearls
| Criterion | Oxagile | 10Pearls |
|---|---|---|
| Minimum engagement | $25K | $30K |
| Engagement models | Fixed project, T&M, Dedicated team | Fixed project, Dedicated team, T&M |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Oxagile vs 10Pearls
| Dimension | Oxagile | 10Pearls |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | media, advertising, retail | healthcare, financial services, government |
| Best use cases | Video content analysis ML for content moderation, tagging, or recommendation, Computer vision model development for sports performance analysis | Federal government AI programme delivery with security clearance-compatible development practices, Healthcare ML development for clinical analytics under HIPAA constraints |
| Typical project type | Fixed project | Fixed project |
Oxagile vs 10Pearls: pros and cons
| 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 |
| 10Pearls | |
|---|---|
| + | CRN Solution Provider 500 recognition (four times) independently validates enterprise AI delivery track record |
| + | Washington DC metro HQ well suited for US federal government ML programmes |
| + | LATAM delivery centers enable nearshore agility in US time zones at competitive rates |
| + | AI-native culture — ML is embedded in the engineering culture, not a separate practice |
| + | Cybersecurity-aware AI development important for government and healthcare buyers |
| - | Less specialist ML boutique depth for highly complex model architecture challenges |
| - | Government and healthcare focus means less consumer-facing ML or retail AI breadth |
| - | Minimum engagement ($30K) is on the higher end for US-based firms of this size |
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.
Who should choose 10Pearls?
10Pearls is the right choice for uS-based enterprises and government contractors needing AI-native delivery teams with North American proximity, government sector experience, and LATAM delivery capacity.
AI-native engineering culture with four CRN Solution Provider 500 recognitions and 1,400+ experts spanning North America and LATAM for enterprise AI programmes. Minimum engagement starts at $30K. Works best with clients in healthcare, financial services, government, retail, logistics.
Decision matrix: Oxagile vs 10Pearls
| 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 | Oxagile |
| Your budget is at the lower end | Oxagile |
| You need specialist depth in a specific vertical | Oxagile |
| 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: Oxagile vs 10Pearls
| Use case | Oxagile fit | 10Pearls fit | Winner |
|---|---|---|---|
| Video content analysis ML for content moderation, tagging, or recommendation | Strong | Limited | Oxagile |
| Computer vision model development for sports performance analysis | Strong | Limited | Oxagile |
| Federal government AI programme delivery with security clearance-compatible development practices | Limited | Strong | 10Pearls |
| Healthcare ML development for clinical analytics under HIPAA constraints | Limited | Strong | 10Pearls |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Oxagile vs 10Pearls
Oxagile (3.8/5) is the stronger overall choice for most Machine Learning Development projects. 20+ years of video domain expertise uniquely positions Oxagile for ML use cases involving video understanding, visual search, and real-time video analytics. It is best for media, AdTech, and sports companies needing ML with deep video processing and computer vision integration backed by 20+ years of video technology expertise.
10Pearls (3.8/5) is the better choice when uS-based enterprises and government contractors needing AI-native delivery teams with North American proximity, government sector experience, and LATAM delivery capacity. If your situation matches those criteria, 10Pearls is a competitive option.
Related comparisons
Oxagile vs 10Pearls FAQ
Is Oxagile better than 10Pearls?
Oxagile (3.8/5) scores higher overall, but "better" depends on your use case. 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. 10Pearls is better for uS-based enterprises and government contractors needing AI-native delivery teams with North American proximity, government sector experience, and LATAM delivery capacity.
How do Oxagile and 10Pearls differ in pricing?
Oxagile uses fixed project, t&m, dedicated team pricing with a minimum engagement of $25K. 10Pearls uses fixed project, dedicated team, t&m pricing with a minimum engagement of $30K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Oxagile or 10Pearls?
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 Oxagile and 10Pearls?
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. 10Pearls's primary differentiator is: ai-native engineering culture with four crn solution provider 500 recognitions and 1,400+ experts spanning north america and latam for enterprise ai programmes. They also differ in team size (250–500 vs 1,400+), minimum engagement ($25K vs $30K), and primary industries served (media, advertising vs healthcare, financial services).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.