MobiDev vs N-iX: full comparison for 2026
Quick verdict
MobiDev (4.4/5) edges ahead of N-iX (4.3/5) overall. MobiDev is the better choice for retail and fitness products, one AI engineer to start. N-iX is the stronger option for enterprises scaling data and ML teams in Europe. The right choice depends on your project size, budget, and required tech stack.
MobiDev vs N-iX: head-to-head summary
| Criterion | MobiDev | N-iX |
|---|---|---|
| Founded | 2009 | 2002 |
| HQ | Atlanta, USA (R&D in Ukraine and Poland) | Lviv, Ukraine (offices across Europe and the Americas) |
| Team size | 201–500 | 2,000–2,500 |
| Rating | 4.4 / 5 | 4.3 / 5 |
| Primary differentiator | Long AI product record in retail, hospitality and fitness | Formal staff-augmentation model backed by a 2,400-person bench |
| Pricing model | Monthly per engineer; dedicated team; rates on request | Time and materials; dedicated team; rates on request |
| Min. engagement | 1 full-time engineer | Not disclosed |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Databricks, Apache Spark |
| Industries served | Retail and e-commerce, Hospitality, Fitness and wellness, Healthcare | Fintech, Manufacturing, Logistics, Healthcare, Telecom |
MobiDev vs N-iX: overview
MobiDev
MobiDev was founded in 2009 in Kharkiv, Ukraine, opened its first U.S. office in Atlanta in 2011, and now runs R&D centers in Ukraine and Łódź, Poland. Its AI team-augmentation offer starts at a single full-time engineer and quotes up to two weeks to allocate someone (per company website; independently unverifiable). The company says 89% of its engineers are middle or senior level and reports more than 65 AI and ML products built, mainly for retail, hospitality, fitness and health clients. Headcount figures range from 201–500 on aggregators to 400+ on a regional IT directory.
N-iX
N-iX started in Lviv, Ukraine, in 2002 and now reports about 2,400 professionals across more than 25 countries in Europe and the Americas. Staff augmentation sits alongside managed teams and full-solution delivery as one of its three cooperation models, and its AI and machine-learning practice is supported by data-engineering and cloud groups. Clutch reviewers describe it as quick to scale teams and good at integrating developers into existing groups. It serves more than 80 active enterprise clients according to a 2026 company overview.
Services and capabilities: MobiDev vs N-iX
| Capability | MobiDev | N-iX |
|---|---|---|
| LLM / GenAI engineers | ✗ | ✗ |
| MLOps & deployment | ✗ | ✓ |
| Computer vision | ✓ | ✗ |
| Data engineering | ✗ | ✓ |
| AI agent development | ✓ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Risk-free trial period | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
Tech stack comparison: MobiDev vs N-iX
| Framework / platform | MobiDev | N-iX |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | N/A |
| AWS SageMaker | N/A | ✓ |
| Azure ML | N/A | ✓ |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: MobiDev vs N-iX
| Criterion | MobiDev | N-iX |
|---|---|---|
| Minimum engagement | 1 full-time engineer | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: MobiDev vs N-iX
| Dimension | MobiDev | N-iX |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail and e-commerce, Hospitality, Fitness and wellness | Fintech, Manufacturing, Logistics |
| Best use cases | Adding a pose-estimation engineer to a fitness app, Placing an AI engineer to build product recommendations for a retailer | Adding data engineers to an enterprise lakehouse program, Staffing an MLOps engineer to productionize existing models |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
MobiDev vs N-iX: pros and cons
| MobiDev | |
|---|---|
| + | You can start with a single engineer instead of a whole squad |
| + | Senior-weighted bench, with a stated six-year average experience among lead AI engineers |
| + | Strong record in computer vision for fitness and sports products |
| + | U.S. and UK incorporation makes contracting straightforward |
| - | Much of the delivery team is in Ukraine, so some buyers will want to discuss continuity planning |
| - | Industry focus is narrower than the large generalists |
| - | No published rates |
| N-iX | |
|---|---|
| + | Large enough to staff data, ML and platform roles from one vendor |
| + | Staff augmentation is a defined product with its own process |
| + | Delivery hubs in several EU countries help with data-residency questions |
| + | Long enterprise client history |
| - | AI is one practice inside a broad software company |
| - | Enterprise sales process can be slow for a single-seat request |
| - | No public rates |
Who should choose MobiDev?
A typical fit: adding a pose-estimation engineer to a fitness app.
Long AI product record in retail, hospitality and fitness. Minimum engagement starts at 1 full-time engineer. Works best with clients in Retail and e-commerce, Hospitality, Fitness and wellness, Healthcare.
Who should choose N-iX?
A typical fit: adding data engineers to an enterprise lakehouse program.
Formal staff-augmentation model backed by a 2,400-person bench. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Manufacturing, Logistics, Healthcare, Telecom.
Decision matrix: MobiDev vs N-iX
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | MobiDev |
| Your budget is at the lower end | Compare: MobiDev (1 full-time engineer) vs N-iX (Not disclosed) |
| 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 | Both may offer discovery engagements |
Use case fit: MobiDev vs N-iX
| Use case | MobiDev fit | N-iX fit | Winner |
|---|---|---|---|
| Adding a pose-estimation engineer to a fitness app | Strong | Strong | Both equally |
| Placing an AI engineer to build product recommendations for a retailer | Strong | Limited | MobiDev |
| Adding data engineers to an enterprise lakehouse program | Strong | Strong | Both equally |
| Staffing an MLOps engineer to productionize existing models | Limited | Strong | N-iX |
Verdict: MobiDev vs N-iX
MobiDev (4.4/5) is the stronger overall choice for most AI Staffing projects. Long AI product record in retail, hospitality and fitness.
N-iX (4.3/5) is worth a look if you need staffing an MLOps engineer to productionize existing models. If your situation matches that, N-iX is a competitive option.
Related comparisons
MobiDev vs N-iX FAQ
Is MobiDev better than N-iX?
MobiDev (4.4/5) scores higher overall, but "better" depends on your use case. MobiDev's strongest advantage: you can start with a single engineer instead of a whole squad. N-iX's strongest advantage: large enough to staff data, ML and platform roles from one vendor.
How do MobiDev and N-iX differ in pricing?
MobiDev uses monthly per engineer; dedicated team; rates on request pricing with a minimum engagement of 1 full-time engineer. N-iX uses time and materials; dedicated team; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: MobiDev or N-iX?
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 agency before shortlisting.
What are the main differences between MobiDev and N-iX?
MobiDev's primary differentiator is: long AI product record in retail, hospitality and fitness. N-iX's primary differentiator is: formal staff-augmentation model backed by a 2,400-person bench. They also differ in team size (201–500 vs 2,000–2,500), minimum engagement (1 full-time engineer vs Not disclosed), and primary industries served (Retail and e-commerce, Hospitality vs Fintech, Manufacturing).
Verify all details directly with each agency before making a decision.