ScienceSoft vs Oxagile: full comparison for 2026
Last updated: July 2026
Quick verdict
ScienceSoft (4.0/5) edges ahead of Oxagile (4.0/5) overall. ScienceSoft is the better choice for manufacturing, healthcare, and oil & gas enterprises needing ISO-certified ML delivery from a stable 35-year-old vendor. Oxagile is the stronger option for media, healthcare, and manufacturing enterprises needing production computer vision or video AI systems. The right choice depends on your project size, budget, and required tech stack.
ScienceSoft vs Oxagile: head-to-head summary
| Criterion | ScienceSoft | Oxagile |
|---|---|---|
| Founded | 1989 | 2005 |
| HQ | McKinney, TX, USA | Minsk, Belarus / Warsaw, Poland |
| Team size | 500–1,000 | 400+ |
| Rating | 4.0 / 5 | 4.0 / 5 |
| Best for | Manufacturing, healthcare, and oil & gas enterprises needing ISO-certified ML delivery from a stable 35-year-old vendor | Media, healthcare, and manufacturing enterprises needing production computer vision or video AI systems |
| Pricing model | Fixed project, T&M, Dedicated team | Fixed project, T&M, Dedicated team |
| Min. engagement | $30K | $25K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | Manufacturing, Healthcare, Financial Services, Logistics, Energy / Oil & Gas | Media / Entertainment, Healthcare, Manufacturing, Technology / SaaS, Logistics |
ScienceSoft vs Oxagile: overview
ScienceSoft
ScienceSoft was founded in 1989 and is headquartered in McKinney, Texas, with a team of 500–1,000 professionals spanning software development, data science, cybersecurity, and IT consulting. Its machine learning practice focuses on manufacturing, healthcare, and oil and gas — regulated industries where domain expertise, compliance knowledge, and long-term support matter more than speed. ScienceSoft's longevity provides clients with an unusually stable vendor relationship: unlike startups or mid-sized boutiques, it has survived multiple technology cycles and carries ISO 9001 and ISO 27001 certifications that many manufacturing and healthcare clients require before signing.
Oxagile
Oxagile was founded in 2005 and operates with primary delivery centres in Minsk, Belarus, and Warsaw, Poland, employing 400+ professionals. The company's AI practice centres on computer vision, LLM integration, ML-supported content analysis, and video processing — capabilities that stem from its long heritage in media technology and video infrastructure for broadcasters and OTT platforms. Oxagile's computer vision work spans automated content moderation for media companies, visual quality inspection for manufacturing, and AI-assisted diagnostics for healthcare, making it one of the more vertically diverse computer vision specialists in this review.
Services and capabilities: ScienceSoft vs Oxagile
| Capability | ScienceSoft | Oxagile |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Deep learning | ✗ | ✗ |
| NLP / Text analytics | ✓ | ✓ |
| Computer vision | ✓ | ✓ |
| MLOps & deployment | ✗ | ✓ |
| Generative AI | ✗ | ✓ |
| AI strategy | ✓ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Fixed-price projects | ✓ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: ScienceSoft vs Oxagile
| Framework / platform | ScienceSoft | Oxagile |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Kubernetes | ✓ | ✓ |
| Databricks | N/A | N/A |
| MLflow | N/A | N/A |
Pricing comparison: ScienceSoft vs Oxagile
| Criterion | ScienceSoft | Oxagile |
|---|---|---|
| Minimum engagement | $30K | $25K |
| Engagement models | Fixed project, Time & materials, Dedicated team | Fixed project, Time & materials, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: ScienceSoft vs Oxagile
| Dimension | ScienceSoft | Oxagile |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Manufacturing, Healthcare, Financial Services | Media / Entertainment, Healthcare, Manufacturing |
| Best use cases | Predictive maintenance ML for manufacturing and industrial equipment with compliance documentation, Medical image analysis and clinical decision support systems for regulated healthcare environments | Automated video content moderation and compliance tagging for OTT and broadcast platforms, Computer vision quality inspection systems for manufacturing production lines |
| Typical project type | Fixed project | Fixed project |
ScienceSoft vs Oxagile: pros and cons
| ScienceSoft | |
|---|---|
| + | 35+ years of operation provides rare vendor stability for enterprises requiring long-term maintenance commitments |
| + | ISO 9001 and ISO 27001 certifications satisfy compliance requirements in manufacturing, healthcare, and regulated industries |
| + | Broad technology stack spans ML, cybersecurity, and traditional software — reduces need for separate vendors on complex projects |
| + | McKinney, TX headquarters provides US-based relationship management for North American enterprise clients |
| + | Competitively priced relative to US-headquartered firms of comparable certification status |
| - | ML is one practice within a very broad portfolio — specialist depth in cutting-edge deep learning is thinner than ML-native boutiques |
| - | Conservative delivery style suits compliance-heavy industries but can slow projects where experimentation and iteration are prioritised |
| - | Less suitable for startups needing fast ML prototyping or cutting-edge generative AI capability |
| Oxagile | |
|---|---|
| + | 20-year computer vision heritage provides production-grade depth in a capability most generalists offer only superficially |
| + | Video AI and content analysis capability is particularly strong — directly transferable to media and broadcast clients |
| + | Dual delivery centre model (Minsk + Warsaw) provides redundancy and EU data processing alignment via Warsaw |
| + | Full project lifecycle from CV prototype through production deployment and monitoring |
| + | Competitive rates relative to Western European firms of equivalent computer vision depth |
| - | Minsk-based delivery introduces political and banking risk for some Western European and North American clients |
| - | Core strength is computer vision and media AI; pure NLP or tabular ML projects may receive less specialised teams |
| - | Less established for cloud-native MLOps and generative AI relative to newer AI-native firms |
Who should choose ScienceSoft?
ScienceSoft is the right choice for manufacturing, healthcare, and oil & gas enterprises needing ISO-certified ML delivery from a stable 35-year-old vendor.
35+ years of operation with ISO 9001 and ISO 27001 certifications — provides compliance-mandated vendor stability rare in the ML agency market. Minimum engagement starts at $30K. Works best with clients in Manufacturing, Healthcare, Financial Services, Logistics, Energy / Oil & Gas.
Who should choose Oxagile?
Oxagile is the right choice for media, healthcare, and manufacturing enterprises needing production computer vision or video AI systems.
20-year heritage in video technology and media AI translates directly into best-in-class computer vision delivery for media, broadcast, and content platforms. Minimum engagement starts at $25K. Works best with clients in Media / Entertainment, Healthcare, Manufacturing, Technology / SaaS, Logistics.
Decision matrix: ScienceSoft vs Oxagile
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | ScienceSoft |
| You need a large dedicated team for an ongoing programme | ScienceSoft |
| Your budget is at the lower end | Oxagile |
| You need specialist depth in a specific vertical | ScienceSoft |
| 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: ScienceSoft vs Oxagile
| Use case | ScienceSoft fit | Oxagile fit | Winner |
|---|---|---|---|
| Predictive maintenance ML for manufacturing and industrial equipment with compliance documentation | Strong | Limited | ScienceSoft |
| Medical image analysis and clinical decision support systems for regulated healthcare environments | Strong | Strong | Both equally |
| Automated video content moderation and compliance tagging for OTT and broadcast platforms | Limited | Strong | Oxagile |
| Computer vision quality inspection systems for manufacturing production lines | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: ScienceSoft vs Oxagile
ScienceSoft (4.0/5) is the stronger overall choice for most Machine Learning projects. 35+ years of operation with ISO 9001 and ISO 27001 certifications — provides compliance-mandated vendor stability rare in the ML agency market. It is best for manufacturing, healthcare, and oil & gas enterprises needing ISO-certified ML delivery from a stable 35-year-old vendor.
Oxagile (4.0/5) is the better choice when media, healthcare, and manufacturing enterprises needing production computer vision or video AI systems. If your situation matches those criteria, Oxagile is a competitive option.
Related comparisons
ScienceSoft vs Oxagile FAQ
Is ScienceSoft better than Oxagile?
ScienceSoft (4.0/5) scores higher overall, but "better" depends on your use case. ScienceSoft is better for manufacturing, healthcare, and oil & gas enterprises needing ISO-certified ML delivery from a stable 35-year-old vendor. Oxagile is better for media, healthcare, and manufacturing enterprises needing production computer vision or video AI systems.
How do ScienceSoft and Oxagile differ in pricing?
ScienceSoft uses fixed project, t&m, dedicated team 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: ScienceSoft or Oxagile?
ScienceSoft is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between ScienceSoft and Oxagile?
ScienceSoft's primary differentiator is: 35+ years of operation with iso 9001 and iso 27001 certifications — provides compliance-mandated vendor stability rare in the ml agency market. Oxagile's primary differentiator is: 20-year heritage in video technology and media ai translates directly into best-in-class computer vision delivery for media, broadcast, and content platforms. They also differ in team size (500–1,000 vs 400+), minimum engagement ($30K vs $25K), and primary industries served (Manufacturing, Healthcare vs Media / Entertainment, Healthcare).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.