EPAM Systems vs InData Labs: full comparison for 2026
Quick verdict
EPAM Systems (4.1/5) edges ahead of InData Labs (4.1/5) overall. EPAM Systems is the better choice for enterprises with multi-year engineering budgets. InData Labs is the stronger option for smaller budgets, analytics and document AI. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs InData Labs: head-to-head summary
| Criterion | EPAM Systems | InData Labs |
|---|---|---|
| Founded | 1993 | 2014 |
| HQ | Newtown, PA, USA | Nicosia, Cyprus |
| Team size | 61,000+ | 80+ |
| Rating | 4.1 / 5 | 4.1 / 5 |
| Primary differentiator | Engineering capacity across Europe, India, and the Americas for long AI programs | Predictive analytics depth at mid-band European rates |
| Pricing model | Time & materials and dedicated teams; rates on request | Fixed-scope projects and time & materials; $50–$99/hr (directory listings) |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Azure OpenAI, AWS Bedrock, Databricks | Python, Azure OpenAI, AWS Bedrock |
| Industries served | Financial services, Healthcare, Retail & e-commerce, Media, Energy | Retail & e-commerce, Healthcare, Financial services, Media |
EPAM Systems vs InData Labs: overview
EPAM Systems
EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with over 61,200 employees at the end of 2025. Acquisitions shaped the recent mix: NEORIS (2024) for Latin America and Iberia, and First Derivative (completed December 2024) for financial-services data. Management targets more than $600 million of AI-native revenue in 2026, after reporting over $105 million in Q4 2025. Its AI/Run tooling and Agentic QA product support large engineering programs more than single-workflow pilots.
InData Labs
InData Labs is a data science and AI company founded in 2014 and headquartered in Nicosia, Cyprus, with about 80 specialists. It builds predictive analytics, natural language processing, and computer vision systems, and more recently LLM integrations into client products. Directory listings show a $50–$99 hourly band and a $10,000 starting project size, though its own Clutch figures weren't confirmed. Small teams wanting analytics or document AI without enterprise overhead will find it a reasonable fit.
Services and capabilities: EPAM Systems vs InData Labs
| Capability | EPAM Systems | InData Labs |
|---|---|---|
| CRM / ERP integration | ✓ | ✗ |
| LLM API gateway & cost control | ✓ | ✓ |
| Document processing | ✗ | ✓ |
| Conversational AI | ✗ | ✓ |
| Agentic workflows | ✓ | ✗ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✓ | ✗ |
Tech stack comparison: EPAM Systems vs InData Labs
| Framework / platform | EPAM Systems | InData Labs |
|---|---|---|
| Salesforce | N/A | N/A |
| SAP | ✓ | N/A |
| Microsoft Dynamics 365 | N/A | N/A |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | N/A |
| Databricks | ✓ | N/A |
| BigQuery | N/A | ✓ |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | ✓ | ✓ |
| Zendesk | N/A | N/A |
Pricing comparison: EPAM Systems vs InData Labs
| Criterion | EPAM Systems | InData Labs |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Time & materials, Dedicated team, Managed services | Fixed-scope project, Time & materials |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs InData Labs
| Dimension | EPAM Systems | InData Labs |
|---|---|---|
| Best company size | Enterprise | Startup to mid-market |
| Best industries | Financial services, Healthcare, Retail & e-commerce | Retail & e-commerce, Healthcare, Financial services |
| Best use cases | Large data-platform programs that end in AI features, Agent development across several business units | Churn and demand models for a mid-size retailer, Document classification for a healthcare provider |
| Typical project type | Time & materials | Fixed-scope project |
EPAM Systems vs InData Labs: pros and cons
| EPAM Systems | |
|---|---|
| + | Engineering depth to staff many workstreams at once. |
| + | Public reporting on AI-native revenue gives a measurable view of the practice. |
| + | First Derivative added capital-markets data skills. |
| + | Agentic QA product addresses testing of AI-generated code. |
| - | Acquisition-driven growth (NEORIS, First Derivative) means teams are still being integrated |
| - | Not built for a small fixed-price pilot |
| - | Management flagged slower organic growth in 2026 guidance |
| InData Labs | |
|---|---|
| + | Rates sit in the middle band while the team stays senior. |
| + | Over a decade of predictive modeling before the LLM wave. |
| + | Small enough that the founders stay close to projects. |
| + | Covers computer vision as well as text. |
| - | Its team of about 80 limits parallel workstreams |
| - | No CRM or ERP partner credentials |
| - | Pricing figures come from directories, not a confirmed Clutch profile |
Who should choose EPAM Systems?
A typical fit: large data-platform programs that end in AI features.
Engineering capacity across Europe, India, and the Americas for long AI programs. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media, Energy.
Who should choose InData Labs?
A typical fit: churn and demand models for a mid-size retailer.
Predictive analytics depth at mid-band European rates. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Healthcare, Financial services, Media.
Decision matrix: EPAM Systems vs InData Labs
| Your situation | Recommended choice |
|---|---|
| You want a priced pilot before committing to a rollout | Neither advertises one; ask for a scoped pilot quote |
| You need someone to run and monitor the system after launch | EPAM Systems |
| Your budget is at the lower end | Compare: EPAM Systems (Not disclosed) vs InData Labs (Not disclosed) |
| The AI has to read and write in your CRM or ERP | EPAM Systems |
| You need multi-step agents acting across systems | EPAM Systems |
| You need a large team for a multi-year program | EPAM Systems |
Use case fit: EPAM Systems vs InData Labs
| Use case | EPAM Systems fit | InData Labs fit | Winner |
|---|---|---|---|
| Large data-platform programs that end in AI features | Strong | Limited | EPAM Systems |
| Agent development across several business units | Strong | Limited | EPAM Systems |
| Churn and demand models for a mid-size retailer | Limited | Strong | InData Labs |
| Document classification for a healthcare provider | Limited | Strong | InData Labs |
Verdict: EPAM Systems vs InData Labs
EPAM Systems (4.1/5) is the stronger overall choice for most AI Integration Services projects. Engineering capacity across Europe, India, and the Americas for long AI programs.
InData Labs (4.1/5) is worth a look if you need document classification for a healthcare provider. If your situation matches that, InData Labs is a competitive option.
Related comparisons
EPAM Systems vs InData Labs FAQ
Is EPAM Systems better than InData Labs?
EPAM Systems (4.1/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: engineering depth to staff many workstreams at once. InData Labs's strongest advantage: rates sit in the middle band while the team stays senior.
How do EPAM Systems and InData Labs differ in pricing?
EPAM Systems's pricing: time & materials and dedicated teams; rates on request. InData Labs's pricing: fixed-scope projects and time & materials; $50–$99/hr (directory listings). Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
Which is better for enterprise: EPAM Systems or InData Labs?
EPAM Systems is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each provider before shortlisting.
What are the main differences between EPAM Systems and InData Labs?
EPAM Systems's primary differentiator is: engineering capacity across Europe, India, and the Americas for long AI programs. InData Labs's primary differentiator is: predictive analytics depth at mid-band European rates. They also differ in team size (61,000+ vs 80+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Retail & e-commerce, Healthcare).
Verify all details directly with each provider before making a decision.