InData Labs vs MobiDev: full comparison for 2026
Quick verdict
InData Labs (4.5/5) edges ahead of MobiDev (4.2/5) overall. InData Labs is the better choice for Fintech, healthcare, SaaS — specialist data-science boutique. MobiDev is the stronger option for Retail, hospitality, fitness companies — proven mid-size AI delivery. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs MobiDev: head-to-head summary
| Criterion | InData Labs | MobiDev |
|---|---|---|
| Founded | 2014 | 2009 |
| HQ | Nicosia, Cyprus | Atlanta, Georgia, USA |
| Team size | 51–200 | 201–500 |
| Rating | 4.5 / 5 | 4.2 / 5 |
| Primary differentiator | Dedicated in-house R&D center focused specifically on data science and AI rather than broad software outsourcing | 65+ delivered AI/ML products concentrated in retail, hospitality, fitness, and health/wellness verticals |
| Pricing model | Fixed project and Time & Material | Fixed project and dedicated team |
| Min. engagement | $20K | $20K |
| Primary tech stack | Python, Scikit-learn, TensorFlow | Python, TensorFlow, OpenCV |
| Industries served | FinTech, Healthcare, Technology/SaaS, Retail, Logistics | Retail, Hospitality, Health & Fitness, Sports |
InData Labs vs MobiDev: overview
InData Labs
InData Labs is a data science and AI consultancy founded in 2014 by Marat Karpeko, headquartered in Nicosia, Cyprus, with additional offices in Lithuania and the US. The 80+ person firm (per company website) runs its own R&D center and focuses on production AI systems for fintech, healthcare, SaaS, retail, and logistics clients.
MobiDev
MobiDev is a custom software development company founded in 2009, headquartered in Atlanta, Georgia, with R&D centers in Lodz, Poland and Chernivtsi, Ukraine, and roughly 290–400 engineers. CEO Oleg Lola initiated a dedicated AI/ML practice in 2018, and the company has since delivered more than 65 AI/ML products, concentrated in retail, hospitality, fitness, sports, and health/wellness.
Services and capabilities: InData Labs vs MobiDev
| Capability | InData Labs | MobiDev |
|---|---|---|
| Custom ML model development | ✓ | ✓ |
| Deep learning & computer vision | ✗ | ✓ |
| NLP & LLM / Generative AI | ✗ | ✗ |
| MLOps & production deployment | ✗ | ✗ |
| Data engineering | ✓ | ✓ |
| AI strategy consulting | ✓ | ✗ |
| Staff augmentation | ✗ | ✓ |
Tech stack comparison: InData Labs vs MobiDev
| Framework / platform | InData Labs | MobiDev |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| Databricks | N/A | N/A |
| LangChain | N/A | N/A |
Pricing comparison: InData Labs vs MobiDev
| Criterion | InData Labs | MobiDev |
|---|---|---|
| Minimum engagement | $20K | $20K |
| Engagement models | Fixed project, Time & Material | Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: InData Labs vs MobiDev
| Dimension | InData Labs | MobiDev |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Healthcare, Technology/SaaS | Retail, Hospitality, Health & Fitness |
| Best use cases | Building a fintech risk-scoring or fraud model with a specialist data-science team, Standing up a healthcare predictive-analytics pilot with a boutique partner | Retail or hospitality companies wanting computer-vision or recommendation features built into an existing product, Health and fitness apps needing an ML-driven personalization or tracking feature |
| Typical project type | Fixed project | Fixed project |
InData Labs vs MobiDev: pros and cons
| InData Labs | |
|---|---|
| + | Founder brought data-analytics experience from the gaming industry, an unusually data-intensive prior domain |
| + | Multi-country footprint (Cyprus, Lithuania, US) without the very large headcount of enterprise IT firms |
| + | 10+ years of focused data science practice rather than a recent AI pivot from generalist dev work |
| + | Named vertical focus (FinTech, Healthcare, Logistics) supports domain-specific model design |
| - | 80-person team limits capacity for very large multi-year enterprise programs |
| - | Less brand recognition in North America than US-headquartered competitors |
| - | Public case studies rarely disclose named enterprise clients |
| MobiDev | |
|---|---|
| + | 65+ delivered AI/ML products gives a concrete, countable delivery track record rather than general marketing claims |
| + | Deliberate AI/ML practice build-out since 2018, rather than a very recent pivot |
| + | Named vertical concentration (retail, hospitality, fitness, health) supports domain-specific product experience |
| + | Mid-size team (290–400) balances specialist focus with real delivery capacity |
| - | Narrower industry focus than horizontal AI consultancies serving finance, healthcare, and manufacturing broadly |
| - | Smaller scale than the large enterprise IT firms on this list, limiting very large multi-team programs |
| - | AI/ML sits alongside a broader general custom-software-development practice |
Who should choose InData Labs?
A typical fit: building a fintech risk-scoring or fraud model with a specialist data-science team.
Dedicated in-house R&D center focused specifically on data science and AI rather than broad software outsourcing. Minimum engagement starts at $20K. Works best with clients in FinTech, Healthcare, Technology/SaaS, Retail, Logistics.
Who should choose MobiDev?
A typical fit: retail or hospitality companies wanting computer-vision or recommendation features built into an existing product.
65+ delivered AI/ML products concentrated in retail, hospitality, fitness, and health/wellness verticals. Minimum engagement starts at $20K. Works best with clients in Retail, Hospitality, Health & Fitness, Sports.
Decision matrix: InData Labs vs MobiDev
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | InData Labs |
| You need a large dedicated team for an ongoing programme | MobiDev |
| Your budget is at the lower end | InData Labs |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | InData Labs |
Use case fit: InData Labs vs MobiDev
| Use case | InData Labs fit | MobiDev fit | Winner |
|---|---|---|---|
| Building a fintech risk-scoring or fraud model with a specialist data-science team | Strong | Limited | InData Labs |
| Standing up a healthcare predictive-analytics pilot with a boutique partner | Strong | Limited | InData Labs |
| Retail or hospitality companies wanting computer-vision or recommendation features built into an existing product | Strong | Strong | Both equally |
| Health and fitness apps needing an ML-driven personalization or tracking feature | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs MobiDev
InData Labs (4.5/5) is the stronger overall choice for most Machine Learning Development projects. Dedicated in-house R&D center focused specifically on data science and AI rather than broad software outsourcing.
MobiDev (4.2/5) is worth a look if you need health and fitness apps needing an ML-driven personalization or tracking feature. If your situation matches that, MobiDev is a competitive option.
Related comparisons
InData Labs vs MobiDev FAQ
Is InData Labs better than MobiDev?
InData Labs (4.5/5) scores higher overall, but "better" depends on your use case. InData Labs's strongest advantage: founder brought data-analytics experience from the gaming industry, an unusually data-intensive prior domain. MobiDev's strongest advantage: 65+ delivered AI/ML products gives a concrete, countable delivery track record rather than general marketing claims.
How do InData Labs and MobiDev differ in pricing?
InData Labs uses fixed project and time & material pricing with a minimum engagement of $20K. MobiDev uses fixed project and dedicated team pricing with a minimum engagement of $20K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: InData Labs or MobiDev?
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 InData Labs and MobiDev?
InData Labs's primary differentiator is: dedicated in-house R&D center focused specifically on data science and AI rather than broad software outsourcing. MobiDev's primary differentiator is: 65+ delivered AI/ML products concentrated in retail, hospitality, fitness, and health/wellness verticals. They also differ in team size (51–200 vs 201–500), minimum engagement ($20K vs $20K), and primary industries served (FinTech, Healthcare vs Retail, Hospitality).