InData Labs vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.5/5) edges ahead of EPAM Systems (3.8/5) 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.. EPAM Systems is the stronger option for the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner.. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs EPAM Systems: head-to-head summary
| Criterion | InData Labs | EPAM Systems |
|---|---|---|
| Founded | 2014 | 1993 |
| HQ | Nicosia, Cyprus | Newtown, Pennsylvania, USA |
| Team size | 51–200 | 10,000+ |
| Rating | 4.5 / 5 | 3.8 / 5 |
| Best for | Fintech, healthcare, and SaaS companies wanting a specialist data-science boutique rather than a generalist software vendor. | The largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner. |
| Pricing model | Fixed project and Time & Material | Managed services and fixed project |
| Min. engagement | $20K | Not published |
| Primary tech stack | Python, Scikit-learn, TensorFlow | Python, EPAM DIAL, Azure OpenAI |
| Industries served | FinTech, Healthcare, Technology/SaaS, Retail, Logistics | Financial Services, Healthcare, Retail, Technology/SaaS, Government |
InData Labs vs EPAM Systems: 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.
EPAM Systems
EPAM Systems is a global digital engineering company founded in 1993 by Arkadiy Dobkin and Leo Lozner, listed on the NYSE since 2012, with approximately 62,850 employees as of end of 2025. The company has built a proprietary AI orchestration platform, EPAM DIAL, for managing large language models in production, but AI/ML delivery represents one part of an enormous, broadly diversified enterprise engineering portfolio.
Services and capabilities: InData Labs vs EPAM Systems
| Capability | InData Labs | EPAM Systems |
|---|---|---|
| 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 EPAM Systems
| Framework / platform | InData Labs | EPAM Systems |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | ✓ |
| Databricks | N/A | N/A |
| LangChain | N/A | N/A |
Pricing comparison: InData Labs vs EPAM Systems
| Criterion | InData Labs | EPAM Systems |
|---|---|---|
| Minimum engagement | $20K | Not published |
| Engagement models | Fixed project, Time & Material | Managed services, Fixed project, Staff augmentation |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Enterprise / not published |
Target audience comparison: InData Labs vs EPAM Systems
| Dimension | InData Labs | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | FinTech, Healthcare, Technology/SaaS | Financial Services, Healthcare, Retail |
| 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 | Global enterprises needing AI delivered at a scale only a 60,000+ employee firm can support, Programs that specifically want to leverage the EPAM DIAL LLM orchestration platform |
| Typical project type | Fixed project | Managed services |
InData Labs vs EPAM Systems: 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 |
| EPAM Systems | |
|---|---|
| + | Largest, most globally distributed team on this list, supporting essentially unlimited program scale |
| + | NYSE listing (since 2012) provides the highest level of public financial transparency among firms reviewed here |
| + | Proprietary EPAM DIAL platform for LLM orchestration shows real internal AI infrastructure investment |
| + | 32 years of continuous operation across more than 55 countries |
| - | AI/ML is a specialization within an enormous generalist engineering portfolio, not the company's defining focus |
| - | Scale of the organization can translate into higher account-management overhead for smaller engagements |
| - | Buyers wanting a boutique, founder-accessible relationship will find that better served by smaller firms on this list |
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 EPAM Systems?
EPAM Systems is the right choice for the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner..
Largest headcount on this list (62,000+) with NYSE-listed financial transparency and a proprietary LLM orchestration platform (EPAM DIAL).. Minimum engagement starts at Not published. Works best with clients in Financial Services, Healthcare, Retail, Technology/SaaS, Government.
Decision matrix: InData Labs vs EPAM Systems
| 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 | Check each company's engagement model |
| Your budget is at the lower end | Compare: InData Labs ($20K) vs EPAM Systems (Not published) |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | EPAM Systems |
| You need consulting before committing to a build | InData Labs |
Use case fit: InData Labs vs EPAM Systems
| Use case | InData Labs fit | EPAM Systems 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 |
| Global enterprises needing AI delivered at a scale only a 60,000+ employee firm can support | Limited | Strong | EPAM Systems |
| Programs that specifically want to leverage the EPAM DIAL LLM orchestration platform | Limited | Strong | EPAM Systems |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs EPAM Systems
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..
EPAM Systems (3.8/5) is the better choice when the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner.. If your situation matches those criteria, EPAM Systems is a competitive option.
Related comparisons
InData Labs vs EPAM Systems FAQ
Is InData Labs better than EPAM Systems?
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.. EPAM Systems is better for the largest global enterprises needing AI delivery embedded inside a massive, publicly traded, multi-service engineering partner..
How do InData Labs and EPAM Systems differ in pricing?
InData Labs uses fixed project and time & material pricing with a minimum engagement of $20K. EPAM Systems uses managed services and 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: InData Labs or EPAM Systems?
InData Labs 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 EPAM Systems?
InData Labs's primary differentiator is: dedicated in-house r&d center focused specifically on data science and ai rather than broad software outsourcing.. EPAM Systems's primary differentiator is: largest headcount on this list (62,000+) with nyse-listed financial transparency and a proprietary llm orchestration platform (epam dial).. They also differ in team size (51–200 vs 10,000+), minimum engagement ($20K vs Not published), and primary industries served (FinTech, Healthcare vs Financial Services, Healthcare).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.