EPAM Systems vs Andersen: full comparison for 2026
Quick verdict
EPAM Systems (4.1/5) edges ahead of Andersen (4.0/5) overall. EPAM Systems is the better choice for enterprises wanting generative AI consulting paired directly with engineering delivery. Andersen is the stronger option for enterprises wanting generative AI consulting paired with broad platform engineering. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs Andersen: head-to-head summary
| Criterion | EPAM Systems | Andersen |
|---|---|---|
| Founded | 1993 | 2007 |
| HQ | Newtown, United States | Warsaw, Poland |
| Team size | 62,000+ | 3,500+ |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Engineering-heavy consulting model, pairing generative AI strategists with the technical build team | 3,500-plus specialists across 20 global offices with a named generative AI consulting practice |
| Pricing model | Retainer or dedicated team, enterprise contracting | Dedicated team or retainer |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, AWS, Azure | Python, .NET, Java |
| Industries served | Financial services, Healthcare, Retail & e-commerce, Media & entertainment | Financial services, Healthcare, Logistics, Automotive |
EPAM Systems vs Andersen: overview
EPAM Systems
EPAM Systems dates to 1993, co-founded in New Jersey and Minsk by Arkadiy Dobkin and Leo Lozner, and has traded on the NYSE as an S&P 500 constituent since 2012. It employed roughly 62,850 people across more than 55 countries at the end of 2025. Generative AI advisory and transformation engineering is a marketed practice area, distinguished from pure Big Four strategy shops by EPAM's engineering-heavy delivery model, pairing generative AI advisors directly with the technical staff who build the resulting systems.
Andersen
Andersen was founded in 2007 and is headquartered in Warsaw, Poland, with more than 3,500 specialists across 20 office locations and 16 development centers globally. Its named AI and data practice covers generative AI consulting, machine learning, data engineering, and robotic process integration, alongside a broader stack spanning .NET, Java, Python, PHP, and Go. Industries served include financial services, healthcare, logistics, automotive, and media.
Services and capabilities: EPAM Systems vs Andersen
| Capability | EPAM Systems | Andersen |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✓ | ✗ |
| Machine learning | ✓ | ✓ |
| Data engineering | ✗ | ✓ |
| MLOps | ✓ | ✗ |
| Fixed-price projects | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: EPAM Systems vs Andersen
| Framework / platform | EPAM Systems | Andersen |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: EPAM Systems vs Andersen
| Criterion | EPAM Systems | Andersen |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Dedicated team, Retainer | Dedicated team, Retainer |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs Andersen
| Dimension | EPAM Systems | Andersen |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Healthcare, Retail & e-commerce | Financial services, Healthcare, Logistics |
| Best use cases | Running a generative AI strategy engagement that needs to transition directly into technical build with the same team., Needing a publicly-traded vendor for audit or procurement compliance reasons. | Running a generative AI consulting initiative that needs to plug into an existing multi-technology enterprise stack., Adding robotic process integration alongside a generative AI consulting engagement. |
| Typical project type | Dedicated team | Dedicated team |
EPAM Systems vs Andersen: pros and cons
| EPAM Systems | |
|---|---|
| + | Public-company financial disclosure that no private consultancy on this list can match. |
| + | Engineering-heavy delivery model avoids the strategy-to-build handoff gap common at pure consultancies. |
| + | Scale to staff several large generative AI consulting and build programs across regions simultaneously. |
| + | S&P 500 membership lets enterprise procurement teams vet it through standard due diligence. |
| - | Generative AI consulting sits inside an enormous engineering business rather than functioning as a dedicated specialty |
| - | Scale generally means slower onboarding and higher minimum engagement than boutique firms |
| Andersen | |
|---|---|
| + | Large global footprint (20 offices, 16 development centers) supports concurrent enterprise programs. |
| + | Named generative AI and data practice, not a generic add-on to broader software services. |
| + | Nearly two decades of software delivery history across multiple technology stacks. |
| + | Vertical coverage spans financial services, healthcare, logistics, and automotive. |
| - | Generative AI consulting is one practice area within a much larger, multi-stack engineering business |
| - | Scale typically means a more formal sales and onboarding process than boutique firms |
Who should choose EPAM Systems?
A typical fit: running a generative AI strategy engagement that needs to transition directly into technical build with the same team.
Engineering-heavy consulting model, pairing generative AI strategists with the technical build team. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media & entertainment.
Who should choose Andersen?
A typical fit: running a generative AI consulting initiative that needs to plug into an existing multi-technology enterprise stack.
3,500-plus specialists across 20 global offices with a named generative AI consulting practice. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Logistics, Automotive.
Decision matrix: EPAM Systems vs Andersen
| 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 Andersen (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 | EPAM Systems |
Use case fit: EPAM Systems vs Andersen
| Use case | EPAM Systems fit | Andersen fit | Winner |
|---|---|---|---|
| Running a generative AI strategy engagement that needs to transition directly into technical build with the same team. | Strong | Strong | Both equally |
| Needing a publicly-traded vendor for audit or procurement compliance reasons. | Strong | Strong | Both equally |
| Running a generative AI consulting initiative that needs to plug into an existing multi-technology enterprise stack. | Strong | Strong | Both equally |
| Adding robotic process integration alongside a generative AI consulting engagement. | Limited | Strong | Andersen |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: EPAM Systems vs Andersen
EPAM Systems (4.1/5) is the stronger overall choice for most Generative AI Consulting projects. Engineering-heavy consulting model, pairing generative AI strategists with the technical build team.
Andersen (4.0/5) is worth a look if you need adding robotic process integration alongside a generative AI consulting engagement. If your situation matches that, Andersen is a competitive option.
Related comparisons
EPAM Systems vs Andersen FAQ
Is EPAM Systems better than Andersen?
EPAM Systems (4.1/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: public-company financial disclosure that no private consultancy on this list can match. Andersen's strongest advantage: large global footprint (20 offices, 16 development centers) supports concurrent enterprise programs.
How do EPAM Systems and Andersen differ in pricing?
EPAM Systems uses retainer or dedicated team, enterprise contracting pricing. Andersen uses dedicated team or retainer 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 Andersen?
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 firm before shortlisting.
What are the main differences between EPAM Systems and Andersen?
EPAM Systems's primary differentiator is: engineering-heavy consulting model, pairing generative AI strategists with the technical build team. Andersen's primary differentiator is: 3,500-plus specialists across 20 global offices with a named generative AI consulting practice. They also differ in team size (62,000+ vs 3,500+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Financial services, Healthcare).
Verify all details directly with each firm before making a decision.