MobiDev vs Xenoss: full comparison for 2026
Quick verdict
MobiDev (4.4/5) edges ahead of Xenoss (4.3/5) overall. MobiDev is the better choice for retail and fitness products, one AI engineer to start. Xenoss is the stronger option for ad-tech and high-volume data teams. The right choice depends on your project size, budget, and required tech stack.
MobiDev vs Xenoss: head-to-head summary
| Criterion | MobiDev | Xenoss |
|---|---|---|
| Founded | 2009 | 2013 |
| HQ | Atlanta, USA (R&D in Ukraine and Poland) | New York, USA |
| Team size | 201–500 | 50–249 |
| Rating | 4.4 / 5 | 4.3 / 5 |
| Primary differentiator | Long AI product record in retail, hospitality and fitness | Data engineers with ad-tech throughput experience |
| Pricing model | Monthly per engineer; dedicated team; rates on request | Time and materials; staff augmentation; rates on request |
| Min. engagement | 1 full-time engineer | Not disclosed |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Apache Spark, Kafka |
| Industries served | Retail and e-commerce, Hospitality, Fitness and wellness, Healthcare | Ad tech, Media, Fintech, Retail and e-commerce |
MobiDev vs Xenoss: 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.
Xenoss
Xenoss was founded in 2013 by ad-tech veterans led by CEO Dmitry Sverdlik and is based in New York, with offices in London and Kyiv. It describes itself as a specialized AI and data-engineering company, and Clutch places it in the 50–249 employee band. Client reviews describe staff augmentation in practice: one London ad-tech client hired Xenoss after failing to find engineers locally, and Xenoss sourced candidates from Ukraine and integrated them into the in-house team. Its background in high-throughput ad-tech systems shows in its data-engineering work.
Services and capabilities: MobiDev vs Xenoss
| Capability | MobiDev | Xenoss |
|---|---|---|
| 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 Xenoss
| Framework / platform | MobiDev | Xenoss |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: MobiDev vs Xenoss
| Criterion | MobiDev | Xenoss |
|---|---|---|
| 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 Xenoss
| Dimension | MobiDev | Xenoss |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail and e-commerce, Hospitality, Fitness and wellness | Ad tech, Media, Fintech |
| Best use cases | Adding a pose-estimation engineer to a fitness app, Placing an AI engineer to build product recommendations for a retailer | Adding streaming-data engineers ahead of an ML launch, Placing ML engineers in a bidding or attribution product |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
MobiDev vs Xenoss: 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 |
| Xenoss | |
|---|---|
| + | Strong on real-time data infrastructure that ML features depend on |
| + | Has placed engineers into UK teams that struggled to hire locally |
| + | Senior leadership comes from the industry it serves most |
| + | Covers both data engineering and model work |
| - | Ad-tech focus is narrower than general AI staffing |
| - | Mid-sized bench |
| - | Rates are not public |
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 Xenoss?
A typical fit: adding streaming-data engineers ahead of an ML launch.
Data engineers with ad-tech throughput experience. Minimum engagement is not publicly disclosed. Works best with clients in Ad tech, Media, Fintech, Retail and e-commerce.
Decision matrix: MobiDev vs Xenoss
| 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 Xenoss (Not disclosed) |
| 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 | Both may offer discovery engagements |
Use case fit: MobiDev vs Xenoss
| Use case | MobiDev fit | Xenoss 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 | Strong | Both equally |
| Adding streaming-data engineers ahead of an ML launch | Strong | Strong | Both equally |
| Placing ML engineers in a bidding or attribution product | Strong | Strong | Both equally |
Verdict: MobiDev vs Xenoss
MobiDev (4.4/5) is the stronger overall choice for most AI Staffing projects. Long AI product record in retail, hospitality and fitness.
Xenoss (4.3/5) is worth a look if you need placing ML engineers in a bidding or attribution product. If your situation matches that, Xenoss is a competitive option.
Related comparisons
MobiDev vs Xenoss FAQ
Is MobiDev better than Xenoss?
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. Xenoss's strongest advantage: strong on real-time data infrastructure that ML features depend on.
How do MobiDev and Xenoss differ in pricing?
MobiDev uses monthly per engineer; dedicated team; rates on request pricing with a minimum engagement of 1 full-time engineer. Xenoss uses time and materials; staff augmentation; 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 Xenoss?
MobiDev 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 Xenoss?
MobiDev's primary differentiator is: long AI product record in retail, hospitality and fitness. Xenoss's primary differentiator is: data engineers with ad-tech throughput experience. They also differ in team size (201–500 vs 50–249), minimum engagement (1 full-time engineer vs Not disclosed), and primary industries served (Retail and e-commerce, Hospitality vs Ad tech, Media).
Verify all details directly with each agency before making a decision.