EPAM Systems vs Globant: full comparison for 2026
Quick verdict
EPAM Systems (4.1/5) edges ahead of Globant (4.0/5) overall. EPAM Systems is the better choice for enterprises adding AI across many products. Globant is the stronger option for US firms wanting nearshore AI engineering. The right choice depends on how far your pilot has got, your budget, and who will run the system after launch.
EPAM Systems vs Globant: head-to-head summary
| Criterion | EPAM Systems | Globant |
|---|---|---|
| Founded | 1993 | 2003 |
| HQ | Newtown, USA | Luxembourg (operations: Buenos Aires) |
| Team size | 61,000+ | 28,500+ |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Engineering capacity to put AI into dozens of products under one program | Nearshore Latin American engineering teams in US time zones |
| Pricing model | Time & materials and dedicated teams; rates not published | Time & materials and dedicated teams; rates not published |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | AWS, Azure, Google Cloud | Google Cloud, AWS, Azure |
| Industries served | Financial services, Healthcare, Retail, Media, Manufacturing | Media, Retail, Financial services, Travel, Healthcare |
EPAM Systems vs Globant: overview
EPAM Systems
EPAM Systems was founded in 1993, is headquartered in Newtown, Pennsylvania, and employs more than 61,000 people. It bought NEORIS and First Derivative in recent years to expand in Latin America and financial services. Its AI work sits inside a large software engineering business, so production AI usually arrives as part of a broader platform or product program. That suits enterprises with many products more than a company with one stalled pilot.
Globant
Globant was founded in 2003 in Buenos Aires, is legally domiciled in Luxembourg, and employs more than 28,500 people. It is listed on the New York Stock Exchange. Its AI work runs through studios that combine design and engineering, with nearshore delivery that keeps time zones close for US clients. Production AI usually comes inside a wider digital product program.
Services and capabilities: EPAM Systems vs Globant
| Capability | EPAM Systems | Globant |
|---|---|---|
| LLM gateway & model routing | ✗ | ✗ |
| Regression tests on prompt and model changes | ✗ | ✗ |
| Canary or staged rollout | ✗ | ✗ |
| Hallucination and drift monitoring | ✗ | ✗ |
| MLOps & model serving | ✓ | ✗ |
| Fixed-scope pilot | ✗ | ✗ |
| Managed run after launch | ✓ | ✗ |
Tech stack comparison: EPAM Systems vs Globant
| Framework / platform | EPAM Systems | Globant |
|---|---|---|
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | ✓ |
| Kubernetes | ✓ | N/A |
| MLflow | N/A | N/A |
| Databricks | ✓ | ✓ |
| Amazon Bedrock | N/A | N/A |
| Vertex AI | N/A | N/A |
| LangChain | N/A | N/A |
| Snowflake | ✓ | N/A |
Pricing comparison: EPAM Systems vs Globant
| Criterion | EPAM Systems | Globant |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Time & materials, Dedicated team, Managed services | Time & materials, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs Globant
| Dimension | EPAM Systems | Globant |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Financial services, Healthcare, Retail | Media, Retail, Financial services |
| Best use cases | AI across a portfolio of enterprise products., Production AI in banking platforms. | AI features inside consumer digital products., Nearshore AI engineering teams for US companies. |
| Typical project type | Time & materials | Time & materials |
EPAM Systems vs Globant: pros and cons
| EPAM Systems | |
|---|---|
| + | Very large engineering bench |
| + | Strong software delivery practice to build on |
| + | Financial-services depth added through First Derivative |
| + | Can run systems after launch |
| - | Recent acquisitions (NEORIS, First Derivative) are still being absorbed |
| - | Too large and slow for one small pilot |
| - | Rates not published |
| Globant | |
|---|---|
| + | Nearshore teams share working hours with US clients |
| + | Large design and engineering capacity |
| + | Public company with regular disclosures |
| - | AI is one part of a broad digital business |
| - | Large-firm process for small pilots |
| - | Rates not published |
Who should choose EPAM Systems?
A typical fit: AI across a portfolio of enterprise products.
Engineering capacity to put AI into dozens of products under one program. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail, Media, Manufacturing.
Who should choose Globant?
A typical fit: AI features inside consumer digital products.
Nearshore Latin American engineering teams in US time zones. Minimum engagement is not publicly disclosed. Works best with clients in Media, Retail, Financial services, Travel, Healthcare.
Decision matrix: EPAM Systems vs Globant
| Your situation | Recommended choice |
|---|---|
| Your pilot works but nobody trusts it in production yet | Ask each for its release and rollback process |
| Model API spend is growing faster than usage | Neither lists a gateway; ask how cost per feature is tracked |
| You need someone to watch quality after launch | EPAM Systems |
| You run classic ML models that need serving and retraining | EPAM Systems |
| You want a priced pilot before a full rollout | Neither advertises one; ask for a scoped quote |
| Your budget is at the lower end | Compare: EPAM Systems (Not disclosed) vs Globant (Not disclosed) |
| You need a large team for many products at once | EPAM Systems |
Use case fit: EPAM Systems vs Globant
| Use case | EPAM Systems fit | Globant fit | Winner |
|---|---|---|---|
| AI across a portfolio of enterprise products. | Strong | Limited | EPAM Systems |
| Production AI in banking platforms. | Strong | Limited | EPAM Systems |
| AI features inside consumer digital products. | Limited | Strong | Globant |
| Nearshore AI engineering teams for US companies. | Limited | Strong | Globant |
Verdict: EPAM Systems vs Globant
EPAM Systems (4.1/5) is the stronger overall choice for most AI Implementation projects. Engineering capacity to put AI into dozens of products under one program.
Globant (4.0/5) is worth a look if you need nearshore AI engineering teams for US companies. If your situation matches that, Globant is a competitive option.
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EPAM Systems vs Globant FAQ
Is EPAM Systems better than Globant?
EPAM Systems (4.1/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: very large engineering bench. Globant's strongest advantage: nearshore teams share working hours with US clients.
How do EPAM Systems and Globant differ in pricing?
EPAM Systems's pricing: time & materials and dedicated teams; rates not published. Globant's pricing: time & materials and dedicated teams; rates not published. 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 Globant?
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 Globant?
EPAM Systems's primary differentiator is: engineering capacity to put AI into dozens of products under one program. Globant's primary differentiator is: nearshore Latin American engineering teams in US time zones. They also differ in team size (61,000+ vs 28,500+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Media, Retail).
Verify all details directly with each provider before making a decision.