N-iX vs MobiDev: full comparison for 2026
Last updated: July 2026
Quick verdict
N-iX (4.4/5) edges ahead of MobiDev (4.3/5) overall. N-iX is the better choice for enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery.. MobiDev is the stronger option for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. The right choice depends on your project size, budget, and required tech stack.
N-iX vs MobiDev: head-to-head summary
| Criterion | N-iX | MobiDev |
|---|---|---|
| Founded | 2002 | 2009 |
| HQ | Lviv, Ukraine (registered HQ: Valletta, Malta) | Norcross, USA (delivery centers: Lodz, Poland and Chernivtsi, Ukraine) |
| Team size | 1,001–5,000 | 201–500 |
| Rating | 4.4 / 5 | 4.3 / 5 |
| Best for | Enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery. | Small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner. |
| Pricing model | Time & Material, Fixed project | Time & Material, Fixed project |
| Min. engagement | $100,000+ | Not published |
| Primary tech stack | AWS, Microsoft Azure, Google Cloud | Python, Computer vision frameworks, Cloud ML platforms |
| Industries served | Automotive, Telecom, Manufacturing, Transportation | Healthcare, Retail, Manufacturing, Media |
N-iX vs MobiDev: overview
N-iX
N-iX began as Novellix in 2002, building product applications for Novell's Linux platform out of Lviv, Ukraine, and has since grown into a broader software engineering company with a corporate registration in Malta and delivery hubs across Ukraine, Poland, Sweden, and beyond. The company reports more than 2,400 engineers company-wide and states it holds over 350 active cloud certifications across Microsoft, AWS, Google Cloud, Palantir, SAP, and Snowflake. Its dedicated data and AI practice covers machine learning, MLOps, generative AI consulting, and data warehouse/lake architecture, with publicly named enterprise clients including Bosch, Siemens, AutoScout24, and Lebara.
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.
Services and capabilities: N-iX vs MobiDev
| Capability | N-iX | MobiDev |
|---|---|---|
| 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: N-iX vs MobiDev
| Framework / platform | N-iX | MobiDev |
|---|---|---|
| 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 |
| Microsoft Azure | ✓ | N/A |
| Kubernetes | ✓ | ✓ |
| Snowflake | ✓ | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: N-iX vs MobiDev
| Criterion | N-iX | MobiDev |
|---|---|---|
| Minimum engagement | $100,000+ | Not published |
| Engagement models | Time & Material, Fixed project, Dedicated team | Time & Material, Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Enterprise | Mid-market |
Target audience comparison: N-iX vs MobiDev
| Dimension | N-iX | MobiDev |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Automotive, Telecom, Manufacturing | Healthcare, Retail, Manufacturing |
| Best use cases | Building an enterprise-scale data lake or warehouse to feed downstream ML models, Running a large, multi-workstream MLOps implementation across several business units | 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 |
| Typical project type | Time & Material | Time & Material |
N-iX vs MobiDev: pros and cons
| N-iX | |
|---|---|
| + | Clutch rating of 4.8/5 across 35 verified reviews. |
| + | Named, verifiable enterprise clients including Bosch, Siemens, and AutoScout24. |
| + | Broadest multi-cloud certification depth (350+) among the companies researched for this list. |
| + | Maintained delivery continuity through significant regional disruption, per company and press reporting. |
| - | High minimum engagement ($100K+) excludes smaller buyers and early-stage startups. |
| - | Legal HQ (Malta) differs from primary engineering hub (Ukraine), which buyers should clarify during contracting. |
| - | As a multi-service engineering firm, ML/AI competes with several other practice areas for account attention. |
| - | Company-wide headcount (2,400+) makes it harder to gauge the actual size of the ML-specific delivery team. |
| 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. |
Who should choose N-iX?
N-iX is the right choice for enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery..
Broadest cloud certification footprint in this comparison (350+ across five major platforms), backed by a 200+ person dedicated data practice.. Minimum engagement starts at $100,000+. Works best with clients in Automotive, Telecom, Manufacturing, Transportation.
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.
Decision matrix: N-iX vs MobiDev
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | N-iX |
| You need a large dedicated team for an ongoing programme | N-iX |
| Your budget is at the lower end | Compare: N-iX ($100,000+) vs MobiDev (Not published) |
| You need specialist depth in a specific vertical | N-iX |
| 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: N-iX vs MobiDev
| Use case | N-iX fit | MobiDev fit | Winner |
|---|---|---|---|
| Building an enterprise-scale data lake or warehouse to feed downstream ML models | Strong | Strong | Both equally |
| Running a large, multi-workstream MLOps implementation across several business units | Strong | Strong | Both equally |
| Building a custom ML model for a small or medium-sized business without an internal data science team | Strong | Strong | Both equally |
| Combining computer vision or ML work with broader mobile/IoT product development | Limited | Strong | MobiDev |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Limited | N-iX |
Verdict: N-iX vs MobiDev
N-iX (4.4/5) is the stronger overall choice for most ML Model Development projects. Broadest cloud certification footprint in this comparison (350+ across five major platforms), backed by a 200+ person dedicated data practice.. It is best for enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery..
MobiDev (4.3/5) is the better choice when small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. If your situation matches those criteria, MobiDev is a competitive option.
Related comparisons
N-iX vs MobiDev FAQ
Is N-iX better than MobiDev?
N-iX (4.4/5) scores higher overall, but "better" depends on your use case. N-iX is better for enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery.. MobiDev is better for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..
How do N-iX and MobiDev differ in pricing?
N-iX uses time & material, fixed project pricing with a minimum engagement of $100,000+. MobiDev uses time & material, fixed project 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: N-iX or MobiDev?
N-iX 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 N-iX and MobiDev?
N-iX's primary differentiator is: broadest cloud certification footprint in this comparison (350+ across five major platforms), backed by a 200+ person dedicated data practice.. MobiDev's primary differentiator is: historical clutch #1 ranking for machine learning development (2021) combined with a specifically sme-oriented service model.. They also differ in team size (1,001–5,000 vs 201–500), minimum engagement ($100,000+ vs Not published), and primary industries served (Automotive, Telecom vs Healthcare, Retail).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.