Azumo vs EPAM Systems: full comparison for 2026
Quick verdict
Azumo (4.5/5) edges ahead of EPAM Systems (3.9/5) overall. Azumo is the better choice for startups adding GenAI engineers on U.S. hours. EPAM Systems is the stronger option for global enterprises with large, compliance-heavy AI programs. The right choice depends on your project size, budget, and required tech stack.
Azumo vs EPAM Systems: head-to-head summary
| Criterion | Azumo | EPAM Systems |
|---|---|---|
| Founded | 2016 | 1993 |
| HQ | San Francisco, USA | Newtown, Pennsylvania, USA |
| Team size | 100–249 | 62,850 |
| Rating | 4.5 / 5 | 3.9 / 5 |
| Primary differentiator | Nearshore staffing with a hiring focus on GenAI and agent roles | Scale, compliance maturity and vendor certifications |
| Pricing model | Monthly per engineer; dedicated team; project-based; rates on request | Enterprise time and materials; dedicated teams; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | OpenAI, LangChain, Hugging Face | Claude, OpenAI, Gemini |
| Industries served | SaaS, Fintech, Healthcare, Media | Fintech, Healthcare, Retail, Manufacturing, Travel |
Azumo vs EPAM Systems: overview
Azumo
Azumo was founded in San Francisco in 2016 by former investment banker Chike Agbai, whose first client was Twitter. Its engineers are based in more than 20 Latin American countries and work U.S. hours. The company sells three formats: staff augmentation alongside an existing team, dedicated teams, and project delivery, and its recent hiring is weighted toward generative-AI, agent and forward-deployed engineering roles. Headcount estimates range from about 80 to just over 100 depending on the source.
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.
Services and capabilities: Azumo vs EPAM Systems
| Capability | Azumo | EPAM Systems |
|---|---|---|
| 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: Azumo vs EPAM Systems
| Framework / platform | Azumo | EPAM Systems |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | ✓ |
| AWS SageMaker | N/A | ✓ |
| Azure ML | ✓ | ✓ |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Azumo vs EPAM Systems
| Criterion | Azumo | EPAM Systems |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Azumo vs EPAM Systems
| Dimension | Azumo | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, Healthcare | Fintech, Healthcare, Retail |
| Best use cases | Adding an LLM engineer to ship a first GenAI feature, Hiring an agent developer to prototype internal automation | Staffing a multi-team GenAI program at a global bank, Adding certified Claude engineers to an enterprise AI platform |
| Typical project type | Full-time dedicated engineers | Dedicated team |
Azumo vs EPAM Systems: pros and cons
| Azumo | |
|---|---|
| + | Hiring pattern shows real investment in LLM and agent engineering, beyond generic web developers |
| + | No long-term commitment required for augmentation seats |
| + | U.S. time zones and a U.S.-based management team |
| + | Small enough that founders and senior staff stay involved in client accounts |
| - | Headcount is modest, so very large teams may take longer to assemble |
| - | Public detail on how candidates are technically screened is thin |
| - | No published rates |
| 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 |
Who should choose Azumo?
A typical fit: adding an LLM engineer to ship a first GenAI feature.
Nearshore staffing with a hiring focus on GenAI and agent roles. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Fintech, Healthcare, Media.
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.
Decision matrix: Azumo 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 | Azumo |
| Your budget is at the lower end | Compare: Azumo (Not disclosed) vs EPAM Systems (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: Azumo vs EPAM Systems
| Use case | Azumo fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Adding an LLM engineer to ship a first GenAI feature | Strong | Strong | Both equally |
| Hiring an agent developer to prototype internal automation | Strong | Limited | Azumo |
| Staffing a multi-team GenAI program at a global bank | Limited | Strong | EPAM Systems |
| Adding certified Claude engineers to an enterprise AI platform | Strong | Strong | Both equally |
Verdict: Azumo vs EPAM Systems
Azumo (4.5/5) is the stronger overall choice for most AI Staffing projects. Nearshore staffing with a hiring focus on GenAI and agent roles.
EPAM Systems (3.9/5) is worth a look if you need adding certified Claude engineers to an enterprise AI platform. If your situation matches that, EPAM Systems is a competitive option.
Related comparisons
Azumo vs EPAM Systems FAQ
Is Azumo better than EPAM Systems?
Azumo (4.5/5) scores higher overall, but "better" depends on your use case. Azumo's strongest advantage: hiring pattern shows real investment in LLM and agent engineering, beyond generic web developers. EPAM Systems's strongest advantage: largest bench on this list, with security and compliance processes to match.
How do Azumo and EPAM Systems differ in pricing?
Azumo uses monthly per engineer; dedicated team; project-based; rates on request pricing. EPAM Systems uses enterprise time and materials; dedicated teams; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Azumo or EPAM Systems?
Azumo 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 Azumo and EPAM Systems?
Azumo's primary differentiator is: nearshore staffing with a hiring focus on GenAI and agent roles. EPAM Systems's primary differentiator is: Scale, compliance maturity and vendor certifications. They also differ in team size (100–249 vs 62,850), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (SaaS, Fintech vs Fintech, Healthcare).
Verify all details directly with each agency before making a decision.