InData Labs vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.5/5) edges ahead of DataArt (3.9/5) overall. InData Labs is the better choice for fintech, healthcare, and SaaS companies wanting a specialist data-science boutique rather than a generalist software vendor.. DataArt is the stronger option for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs DataArt: head-to-head summary
| Criterion | InData Labs | DataArt |
|---|---|---|
| Founded | 2014 | 1997 |
| HQ | Nicosia, Cyprus | New York, USA |
| Team size | 51–200 | 5,001–10,000 |
| Rating | 4.5 / 5 | 3.9 / 5 |
| Best for | Fintech, healthcare, and SaaS companies wanting a specialist data-science boutique rather than a generalist software vendor. | Enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner. |
| Pricing model | Fixed project and Time & Material | Fixed project, dedicated team, staff augmentation |
| Min. engagement | $20K | Not published |
| Primary tech stack | Python, Scikit-learn, TensorFlow | Python, Azure OpenAI, AWS |
| Industries served | FinTech, Healthcare, Technology/SaaS, Retail, Logistics | Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality |
InData Labs vs DataArt: 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.
DataArt
DataArt is a software engineering and consulting company founded in 1997 in New York by Eugene Goland, with roughly 5,400 employees across more than 30 locations spanning the US, Europe, Latin America, India, and the UAE. The firm added an Advanced AI Strategy Consulting service line in 2024, delivering data, analytics, and AI/ML work alongside its long-standing core software engineering practice.
Services and capabilities: InData Labs vs DataArt
| Capability | InData Labs | DataArt |
|---|---|---|
| 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 DataArt
| Framework / platform | InData Labs | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| Databricks | N/A | ✓ |
| LangChain | N/A | N/A |
Pricing comparison: InData Labs vs DataArt
| Criterion | InData Labs | DataArt |
|---|---|---|
| Minimum engagement | $20K | Not published |
| Engagement models | Fixed project, Time & Material | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Enterprise / not published |
Target audience comparison: InData Labs vs DataArt
| Dimension | InData Labs | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | FinTech, Healthcare, Technology/SaaS | Financial Services, Media & Entertainment, Healthcare |
| 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 | Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery, Media or travel companies needing broad-based data and AI/ML capability |
| Typical project type | Fixed project | Fixed project |
InData Labs vs DataArt: 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 |
| DataArt | |
|---|---|
| + | 28 years of continuous operation under the same founder-led leadership |
| + | 30+ global delivery locations across five regions supports broad geographic coverage |
| + | Named AI Strategy Consulting service line launched in 2024 shows deliberate recent AI investment |
| + | Broad industry coverage spanning finance, media, healthcare, and travel |
| - | AI Strategy Consulting is a comparatively recent addition (2024) versus firms with a decade-plus dedicated AI/ML focus |
| - | 5,400-employee scale sits within a broad general software-engineering practice rather than an AI-first firm |
| - | Minimum engagement size not publicly disclosed |
Who should choose InData Labs?
InData Labs is the right choice for fintech, healthcare, and SaaS companies wanting a specialist data-science boutique rather than a generalist software vendor..
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 DataArt?
DataArt is the right choice for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated AI strategy consulting service line.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality.
Decision matrix: InData Labs vs DataArt
| 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 | DataArt |
| Your budget is at the lower end | Compare: InData Labs ($20K) vs DataArt (Not published) |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | DataArt |
| You need consulting before committing to a build | InData Labs |
Use case fit: InData Labs vs DataArt
| Use case | InData Labs fit | DataArt 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 |
| Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery | Limited | Strong | DataArt |
| Media or travel companies needing broad-based data and AI/ML capability | Limited | Strong | DataArt |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs DataArt
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.. It is best for fintech, healthcare, and SaaS companies wanting a specialist data-science boutique rather than a generalist software vendor..
DataArt (3.9/5) is the better choice when enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. If your situation matches those criteria, DataArt is a competitive option.
Related comparisons
InData Labs vs DataArt FAQ
Is InData Labs better than DataArt?
InData Labs (4.5/5) scores higher overall, but "better" depends on your use case. InData Labs is better for fintech, healthcare, and SaaS companies wanting a specialist data-science boutique rather than a generalist software vendor.. DataArt is better for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
How do InData Labs and DataArt differ in pricing?
InData Labs uses fixed project and time & material pricing with a minimum engagement of $20K. DataArt uses fixed project, dedicated team, staff augmentation 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: InData Labs or DataArt?
DataArt 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 DataArt?
InData Labs's primary differentiator is: dedicated in-house r&d center focused specifically on data science and ai rather than broad software outsourcing.. DataArt's primary differentiator is: 28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated ai strategy consulting service line.. They also differ in team size (51–200 vs 5,001–10,000), minimum engagement ($20K vs Not published), and primary industries served (FinTech, Healthcare vs Financial Services, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.