MobiDev vs Xebia: full comparison for 2026
Last updated: July 2026
Quick verdict
MobiDev (4.3/5) edges ahead of Xebia (4.0/5) overall. MobiDev is the better choice for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. Xebia is the stronger option for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. The right choice depends on your project size, budget, and required tech stack.
MobiDev vs Xebia: head-to-head summary
| Criterion | MobiDev | Xebia |
|---|---|---|
| Founded | 2009 | 2001 |
| HQ | Norcross, USA (delivery centers: Lodz, Poland and Chernivtsi, Ukraine) | Amsterdam, Netherlands (US HQ: Atlanta, USA) |
| Team size | 201–500 | 5,001–10,000 |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Best for | Small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner. | Enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery. |
| Pricing model | Time & Material, Fixed project | Not published; enterprise project engagements |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Computer vision frameworks, Cloud ML platforms | Python, Cloud ML platforms (AWS/Azure/GCP), MLOps tooling |
| Industries served | Healthcare, Retail, Manufacturing, Media | Financial services, Retail, Manufacturing, Public sector |
MobiDev vs Xebia: overview
MobiDev
MobiDev is a software development and consulting company founded in 2009, with business units in Norcross, Georgia (US) and Sheffield (UK), and R&D delivery centers in Lodz, Poland and Chernivtsi, Ukraine staffed by more than 400 engineers. Its consulting services span data science, machine learning, augmented reality, IoT, and DevOps, aimed at small and medium-sized companies rather than large enterprises. The company reports a 100 percent project success rate on Upwork and was named the #1 machine learning development company by Clutch in 2021.
Xebia
Xebia was founded in 2001 by Rob Dielemans and Daan Teunissen in the Netherlands and has grown into a global consultancy spanning data and AI, cloud, automation, and software engineering. The Xebia Group reports between 5,000 and 10,000 employees, with corporate headquarters activity in both the Netherlands and Atlanta, Georgia. Its Data & AI Hub practice focuses on turning AI strategy into production-ready solutions, reflecting a repositioning from Xebia's original software craftsmanship and training-company roots toward an AI-first identity.
Services and capabilities: MobiDev vs Xebia
| Capability | MobiDev | Xebia |
|---|---|---|
| Custom model training | ✓ | ✓ |
| Fine-tuning & adaptation | ✗ | ✗ |
| MLOps pipeline | ✗ | ✓ |
| Model deployment & serving | ✗ | ✗ |
| Data engineering for ML | ✓ | ✓ |
| ML infrastructure management | ✗ | ✗ |
| Computer vision | ✓ | ✗ |
| NLP & LLM development | ✗ | ✗ |
| Forecasting & time-series modeling | ✗ | ✗ |
| ML strategy consulting | ✓ | ✓ |
Tech stack comparison: MobiDev vs Xebia
| Framework / platform | MobiDev | Xebia |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Amazon Bedrock | N/A | N/A |
| Google Cloud | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Kubernetes | ✓ | ✓ |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: MobiDev vs Xebia
| Criterion | MobiDev | Xebia |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Time & Material, Fixed project, Dedicated team | Enterprise project engagement, Dedicated team, Training/enablement |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: MobiDev vs Xebia
| Dimension | MobiDev | Xebia |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Healthcare, Retail, Manufacturing | Financial services, Retail, Manufacturing |
| Best use cases | Building a custom ML model for a small or medium-sized business without an internal data science team, Combining computer vision or ML work with broader mobile/IoT product development | Turning an existing AI strategy or pilot into a production-ready, monitored system, Combining technical training/enablement with hands-on AI model development |
| Typical project type | Time & Material | Enterprise project engagement |
MobiDev vs Xebia: pros and cons
| MobiDev | |
|---|---|
| + | Historical Clutch #1 ranking in machine learning development (2021). |
| + | 16 Clutch reviews with consistently positive delivery feedback. |
| + | Explicit focus on small/medium-sized clients, a niche underserved by larger enterprise-first firms. |
| + | Multi-country delivery footprint (Poland, Ukraine) with 400+ engineers provides meaningful bench depth. |
| - | Team-size figures vary by source (roughly 200–500), indicating some reporting inconsistency. |
| - | SME focus may mean less experience with very large, complex enterprise-scale ML platforms. |
| - | Machine learning is one of several practice areas (alongside AR, IoT) rather than the sole focus. |
| - | Minimum engagement size is not published, requiring a scoping conversation. |
| Xebia | |
|---|---|
| + | 25-year software engineering and technical training pedigree underpins its AI delivery credibility. |
| + | Large scale (5,000–10,000 employees) supports substantial enterprise program capacity. |
| + | Explicit focus on production-ready AI rather than strategy-only advisory work. |
| + | Dual US/EU headquarters presence supports transatlantic enterprise clients. |
| - | AI-first repositioning is relatively recent, so its dedicated AI/ML track record is shorter than its overall company history suggests. |
| - | No clearly located aggregate Clutch/G2 star rating in available public sources. |
| - | Pricing model and minimum engagement are not published. |
| - | Large, multi-practice organization means AI/ML delivery quality may vary by regional team. |
Who should choose MobiDev?
MobiDev is the right choice for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..
Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Retail, Manufacturing, Media.
Who should choose Xebia?
Xebia is the right choice for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..
Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone.. Minimum engagement starts at Not published. Works best with clients in Financial services, Retail, Manufacturing, Public sector.
Decision matrix: MobiDev vs Xebia
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | MobiDev |
| You need a large dedicated team for an ongoing programme | MobiDev |
| Your budget is at the lower end | Compare: MobiDev (Not published) vs Xebia (Not published) |
| You need specialist depth in a specific vertical | MobiDev |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | MobiDev |
Use case fit: MobiDev vs Xebia
| Use case | MobiDev fit | Xebia fit | Winner |
|---|---|---|---|
| Building a custom ML model for a small or medium-sized business without an internal data science team | Strong | Limited | MobiDev |
| Combining computer vision or ML work with broader mobile/IoT product development | Strong | Strong | Both equally |
| Turning an existing AI strategy or pilot into a production-ready, monitored system | Limited | Strong | Xebia |
| Combining technical training/enablement with hands-on AI model development | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Limited | Limited | Both equally |
Verdict: MobiDev vs Xebia
MobiDev (4.3/5) is the stronger overall choice for most ML Model Development projects. Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model.. It is best for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..
Xebia (4.0/5) is the better choice when enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. If your situation matches those criteria, Xebia is a competitive option.
Related comparisons
MobiDev vs Xebia FAQ
Is MobiDev better than Xebia?
MobiDev (4.3/5) scores higher overall, but "better" depends on your use case. MobiDev is better for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. Xebia is better for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..
How do MobiDev and Xebia differ in pricing?
MobiDev uses time & material, fixed project pricing with a minimum engagement of Not published. Xebia uses not published; enterprise project engagements pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: MobiDev or Xebia?
Xebia 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 MobiDev and Xebia?
MobiDev's primary differentiator is: historical clutch #1 ranking for machine learning development (2021) combined with a specifically sme-oriented service model.. Xebia's primary differentiator is: quarter-century software craftsmanship and technical training heritage now applied specifically to production ai/ml delivery rather than ai strategy alone.. They also differ in team size (201–500 vs 5,001–10,000), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Retail vs Financial services, Retail).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.