EPAM Systems vs Globant: full comparison for 2026
Quick verdict
EPAM Systems (3.9/5) edges ahead of Globant (3.9/5) overall. EPAM Systems is the better choice for global enterprises with large, compliance-heavy AI programs. Globant is the stronger option for enterprises open to outcome-priced AI delivery. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs Globant: head-to-head summary
| Criterion | EPAM Systems | Globant |
|---|---|---|
| Founded | 1993 | 2003 |
| HQ | Newtown, Pennsylvania, USA | Luxembourg (operations centered in Buenos Aires) |
| Team size | 62,850 | 28,500 |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | Scale, compliance maturity and vendor certifications | Token-subscription pricing in place of seat-based staffing |
| Pricing model | Enterprise time and materials; dedicated teams; rates on request | AI Pods subscription based on token consumption; traditional dedicated teams |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Claude, OpenAI, Gemini | Claude, OpenAI, Gemini |
| Industries served | Fintech, Healthcare, Retail, Manufacturing, Travel | Media, Fintech, Retail, Travel, Healthcare |
EPAM Systems vs Globant: overview
EPAM Systems
EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with about 62,850 employees as of June 30, 2026, of whom roughly 56,650 work in delivery. It reports more than 5,700 Claude-certified engineers and set a target of 10,000, along with thousands of OpenAI- and Gemini-certified specialists. The company is targeting $600 million in AI-native services revenue for 2026. Its model is enterprise delivery, so individual staff augmentation usually sits inside a larger program.
Globant
Globant was founded in Buenos Aires in 2003 and is incorporated in Luxembourg, with about 28,500 employees as of mid-2026. Since June 2025 it has sold AI Pods, a subscription priced on token consumption in which Globant experts supervise AI-agent workflows that produce software. In June 2026 it announced a multi-year alliance with Anthropic and joined the Claude Partner Network as a preferred services partner. The pod model is managed delivery, so buyers looking for classic seat-based staffing should ask about it specifically.
Services and capabilities: EPAM Systems vs Globant
| Capability | EPAM Systems | Globant |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| MLOps & deployment | ✓ | ✗ |
| Computer vision | ✗ | ✗ |
| Data engineering | ✓ | ✗ |
| AI agent development | ✗ | ✓ |
| Fractional / part-time experts | ✗ | ✗ |
| Risk-free trial period | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✓ |
Tech stack comparison: EPAM Systems vs Globant
| Framework / platform | EPAM Systems | Globant |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS SageMaker | ✓ | N/A |
| Azure ML | ✓ | ✓ |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: EPAM Systems vs Globant
| Criterion | EPAM Systems | Globant |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Dedicated team, Managed delivery | Dedicated team, Managed delivery |
| 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 | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Healthcare, Retail | Media, Fintech, Retail |
| Best use cases | Staffing a multi-team GenAI program at a global bank, Adding certified Claude engineers to an enterprise AI platform | Buying AI-assisted engineering capacity on a subscription, Large LatAm-based teams for media and entertainment companies |
| Typical project type | Dedicated team | Dedicated team |
EPAM Systems vs Globant: pros and cons
| EPAM Systems | |
|---|---|
| + | Largest bench on this list, with security and compliance processes to match |
| + | Thousands of engineers certified on major model platforms |
| + | Can staff any role an AI program needs |
| - | Built for enterprise programs; a single-engineer request is a poor fit |
| - | Highest overhead and slowest procurement on this list |
| - | Rates not published |
| Globant | |
|---|---|
| + | Novel pricing model tied to delivered output |
| + | Large LatAm workforce in U.S.-friendly time zones |
| + | Anthropic alliance gives early access to Claude tooling |
| - | Pods are managed delivery; individual augmentation is secondary |
| - | Company is in the middle of a strategy shift after a steep share-price fall |
| - | Enterprise sales cycle |
Who should choose EPAM Systems?
A typical fit: staffing a multi-team GenAI program at a global bank.
Scale, compliance maturity and vendor certifications. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Healthcare, Retail, Manufacturing, Travel.
Who should choose Globant?
A typical fit: buying AI-assisted engineering capacity on a subscription.
Token-subscription pricing in place of seat-based staffing. Minimum engagement is not publicly disclosed. Works best with clients in Media, Fintech, Retail, Travel, Healthcare.
Decision matrix: EPAM Systems vs Globant
| 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 | EPAM Systems |
| Your budget is at the lower end | Compare: EPAM Systems (Not disclosed) vs Globant (Not disclosed) |
| You need specialist depth in a specific vertical | EPAM Systems |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: EPAM Systems vs Globant
| Use case | EPAM Systems fit | Globant fit | Winner |
|---|---|---|---|
| Staffing a multi-team GenAI program at a global bank | Strong | Limited | EPAM Systems |
| Adding certified Claude engineers to an enterprise AI platform | Strong | Limited | EPAM Systems |
| Buying AI-assisted engineering capacity on a subscription | Limited | Strong | Globant |
| Large LatAm-based teams for media and entertainment companies | Limited | Strong | Globant |
Verdict: EPAM Systems vs Globant
EPAM Systems (3.9/5) is the stronger overall choice for most AI Staffing projects. Scale, compliance maturity and vendor certifications.
Globant (3.9/5) is worth a look if you need large LatAm-based teams for media and entertainment companies. If your situation matches that, Globant is a competitive option.
Related comparisons
EPAM Systems vs Globant FAQ
Is EPAM Systems better than Globant?
EPAM Systems (3.9/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: largest bench on this list, with security and compliance processes to match. Globant's strongest advantage: novel pricing model tied to delivered output.
How do EPAM Systems and Globant differ in pricing?
EPAM Systems uses enterprise time and materials; dedicated teams; rates on request pricing. Globant uses ai pods subscription based on token consumption; traditional dedicated teams pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
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 agency before shortlisting.
What are the main differences between EPAM Systems and Globant?
EPAM Systems's primary differentiator is: Scale, compliance maturity and vendor certifications. Globant's primary differentiator is: token-subscription pricing in place of seat-based staffing. They also differ in team size (62,850 vs 28,500), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Fintech, Healthcare vs Media, Fintech).
Verify all details directly with each agency before making a decision.