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 (4.0/5) overall. InData Labs is the better choice for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead.. EPAM Systems is the stronger option for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled 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 | Limassol, Cyprus | Newtown, Pennsylvania, United States |
| Team size | 50–100 | 50,000+ |
| Rating | 4.5 / 5 | 4.0 / 5 |
| Best for | FinTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead. | Large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner. |
| Pricing model | Project-based, dedicated team | Time & materials, managed engagement |
| Min. engagement | Not published | $100,000+ |
| Primary tech stack | Python, TensorFlow, PyTorch | AWS SageMaker, Azure ML, Databricks |
| Industries served | FinTech, Healthcare, Retail & E-commerce, Logistics & Supply Chain | FinTech, Healthcare, Retail & E-commerce, Manufacturing, Telecom |
InData Labs vs EPAM Systems: overview
InData Labs
InData Labs was founded in 2014 by Marat Karpeko and is headquartered in Limassol, Cyprus, with additional offices in Lithuania and the United States. The company has stayed a pure-play AI/data-science consultancy for over a decade, building production ML systems for fintech, healthcare, SaaS, retail, and logistics clients, and is listed in Clutch's Top 10 AI Software Companies leaders matrix. At roughly 80 professionals, it is one of the smaller specialist firms in this list, trading scale for narrower focus.
EPAM Systems
EPAM Systems, Inc. (NYSE: EPAM) has operated since 1993 and has become one of the largest global digital transformation and engineering services providers, with a workforce in the tens of thousands. Its AI development services span generative AI, machine learning consulting, and intelligent automation, delivered by consultants, designers, and engineers who have worked with AI technologies for decades, and Clutch lists a minimum project size of $100,000+ with $150–$199/hr average rates. As a large publicly traded firm, EPAM offers the deepest compliance and financial transparency in this list, at a correspondingly higher entry price point.
Services and capabilities: InData Labs vs EPAM Systems
| Capability | InData Labs | EPAM Systems |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✓ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✓ |
Tech stack comparison: InData Labs vs EPAM Systems
| Framework / platform | InData Labs | EPAM Systems |
|---|---|---|
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| LangChain | N/A | N/A |
| Hugging Face | ✓ | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: InData Labs vs EPAM Systems
| Criterion | InData Labs | EPAM Systems |
|---|---|---|
| Minimum engagement | Not published | $100,000+ |
| Engagement models | Project-based, Dedicated team | Managed engagement, Time & materials, Staff augmentation |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs EPAM Systems
| Dimension | InData Labs | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Healthcare, Retail & E-commerce | FinTech, Healthcare, Retail & E-commerce |
| Best use cases | FinTech company needs predictive analytics built by a team that has done nothing but AI/data science since 2014., Healthcare startup needs a computer vision model with a small, senior delivery team. | Large enterprise with a $100K+ budget needs a publicly traded vendor for AI/ML procurement compliance requirements., Fortune 500 company needs generative AI deployed at global scale with responsible-AI governance built in. |
| Typical project type | Project-based | Managed engagement |
InData Labs vs EPAM Systems: pros and cons
| InData Labs | |
|---|---|
| + | Has operated as a dedicated AI/data science firm since 2014 with no pivot to general software outsourcing. |
| + | Ranked in Clutch's Top 10 AI Software Companies leaders matrix. |
| + | Covers the full pipeline from data engineering through generative AI and computer vision, avoiding narrow single-service lock-in. |
| + | Smaller team size (~80) generally means less account-management overhead between client and engineers. |
| - | At roughly 80 people, InData Labs cannot staff large multi-workstream enterprise programs the way a 2,000+ person firm can. |
| - | Limassol, Cyprus HQ has a thinner regional case-study base in North America compared to US-headquartered peers. |
| EPAM Systems | |
|---|---|
| + | Publicly traded on the NYSE, giving clients access to audited financial disclosures unavailable from private competitors. |
| + | 50,000+ global workforce provides essentially unlimited delivery capacity for the largest enterprise AI programs. |
| + | 31+ years of engineering history (since 1993) predates the current AI hiring wave by decades. |
| + | AI/generative AI practice spans strategy through production deployment and responsible-AI compliance, covering the full enterprise lifecycle. |
| + | Scale/compliance standout among the researched companies — the clearest choice for regulated, large-budget enterprise programs. |
| - | $100,000+ minimum project size (per Clutch) puts EPAM out of reach for startups and mid-market budgets under six figures. |
| - | $150–$199/hr rate band is among the highest in this list, reflecting large-firm overhead. |
| - | At 50,000+ employees, AI/ML is one practice among dozens — clients should confirm they're getting a dedicated AI pod, not a generalist team. |
Who should choose InData Labs?
InData Labs is the right choice for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead..
Ten-plus years as a pure-play AI/data-science firm with no general software-development sideline.. Minimum engagement starts at Not published. Works best with clients in FinTech, Healthcare, Retail & E-commerce, Logistics & Supply Chain.
Who should choose EPAM Systems?
EPAM Systems is the right choice for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner..
Public-company (NYSE: EPAM) scale and compliance rigor, with 30+ years of engineering history predating the AI wave.. Minimum engagement starts at $100,000+. Works best with clients in FinTech, Healthcare, Retail & E-commerce, Manufacturing, Telecom.
Decision matrix: InData Labs vs EPAM Systems
| 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 | InData Labs |
| Your budget is at the lower end | Compare: InData Labs (Not published) vs EPAM Systems ($100,000+) |
| You need specialist depth in a specific vertical | EPAM Systems |
| You need production MLOps support after model launch | EPAM Systems |
| You need consulting before committing to a build | EPAM Systems |
Use case fit: InData Labs vs EPAM Systems
| Use case | InData Labs fit | EPAM Systems fit | Winner |
|---|---|---|---|
| FinTech company needs predictive analytics built by a team that has done nothing but AI/data science since 2014. | Strong | Limited | InData Labs |
| Healthcare startup needs a computer vision model with a small, senior delivery team. | Strong | Strong | Both equally |
| Large enterprise with a $100K+ budget needs a publicly traded vendor for AI/ML procurement compliance requirements. | Limited | Strong | EPAM Systems |
| Fortune 500 company needs generative AI deployed at global scale with responsible-AI governance built in. | Limited | Strong | EPAM Systems |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | 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. Ten-plus years as a pure-play AI/data-science firm with no general software-development sideline.. It is best for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead..
EPAM Systems (4.0/5) is the better choice when large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled 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 that want a decade-old AI specialist without enterprise-scale overhead.. EPAM Systems is better for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner..
How do InData Labs and EPAM Systems differ in pricing?
InData Labs uses project-based, dedicated team pricing with a minimum engagement of Not published. EPAM Systems uses time & materials, managed engagement pricing with a minimum engagement of $100,000+. 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 company before shortlisting.
What are the main differences between InData Labs and EPAM Systems?
InData Labs's primary differentiator is: ten-plus years as a pure-play ai/data-science firm with no general software-development sideline.. EPAM Systems's primary differentiator is: public-company (nyse: epam) scale and compliance rigor, with 30+ years of engineering history predating the ai wave.. They also differ in team size (50–100 vs 50,000+), minimum engagement (Not published vs $100,000+), and primary industries served (FinTech, Healthcare vs FinTech, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.