EPAM Systems vs Simform: full comparison for 2026
Quick verdict
EPAM Systems (4.6/5) edges ahead of Simform (3.8/5) overall. EPAM Systems is the better choice for large enterprises, regulated industries, multi-team AI programs. Simform is the stronger option for cloud-first companies adding AI and data engineers. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs Simform: head-to-head summary
| Criterion | EPAM Systems | Simform |
|---|---|---|
| Founded | 1993 | 2010 |
| HQ | Newtown, Pennsylvania, USA | Orlando, Florida, USA |
| Team size | 61,000+ | 1,000+ |
| Rating | 4.6 / 5 | 3.8 / 5 |
| Primary differentiator | Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes | Cloud and data engineering paired with AI/ML from an India-based bench |
| Pricing model | Time and materials for augmented engineers; dedicated team and managed program contracts; rates on request | Time and materials; dedicated teams; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Azure ML, AWS SageMaker |
| Industries served | Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing | Software & SaaS, Healthcare & life sciences, Retail & e-commerce, Logistics |
EPAM Systems vs Simform: overview
EPAM Systems
EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with roughly 61,000 employees across delivery centers in Europe, the Americas and Asia. It is a public company listed on the New York Stock Exchange. On its Q2 2026 earnings call, management said EPAM had more than 5,700 Anthropic-certified engineers and was among the five largest certified partners worldwide, with AI-native work making up about 11% of revenue. EPAM employs its engineers directly and sells them as augmented capacity, dedicated teams or managed programs, though most large accounts end up in the managed model.
Simform
Simform was founded in 2010 and lists its primary location in Orlando, Florida, with a large delivery center in Ahmedabad, India. Clutch places it in the 1,000 to 9,999 employee range. Its positioning centers on cloud, data, AI/ML and experience engineering, and Clutch reviewers describe staff augmentation engagements covering DevOps, frontend and backend roles.
Services and capabilities: EPAM Systems vs Simform
| Capability | EPAM Systems | Simform |
|---|---|---|
| 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 Simform
| Framework / platform | EPAM Systems | Simform |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Databricks | ✓ | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | ✓ | ✓ |
Pricing comparison: EPAM Systems vs Simform
| Criterion | EPAM Systems | Simform |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs Simform
| Dimension | EPAM Systems | Simform |
|---|---|---|
| Best company size | Mid-market to enterprise | Mid-market to enterprise |
| Best industries | Financial services, Healthcare & life sciences, Retail & e-commerce | Software & SaaS, Healthcare & life sciences, Retail & e-commerce |
| Best use cases | Adding a 15-person GenAI squad to a bank's existing platform team, Rolling out agentic workflows across several business units under one master agreement | Adding an Azure ML engineer to a cloud team, Staffing data engineers for a SaaS analytics feature |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
EPAM Systems vs Simform: pros and cons
| EPAM Systems | |
|---|---|
| + | A Q2 2026 earnings call put its Anthropic-certified engineer count above 5,700, the largest verified GenAI bench on this list |
| + | Public-company reporting, audited financials and mature security reviews make vendor onboarding easier at banks and insurers |
| + | Can staff ten or more AI engineers in parallel across several time zones without running out of senior people |
| + | Deep data-platform practice means LLM work and the data engineering under it can come from one supplier |
| - | Rates are among the highest on this list and are only shared after scoping |
| - | Small requests for one or two engineers rarely get the same attention as large programs |
| - | Engagements tend to drift toward managed delivery, which moves decisions away from your own team |
| Simform | |
|---|---|
| + | Cloud and data skills support production AI |
| + | India-based delivery keeps costs moderate |
| + | Large enough to staff several roles |
| - | Limited working-hour overlap with U.S. teams |
| - | Reviewed augmentation work is mostly general engineering |
| - | AI depth is harder to verify than at specialist firms |
Who should choose EPAM Systems?
A typical fit: adding a 15-person GenAI squad to a bank's existing platform team.
Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing.
Who should choose Simform?
A typical fit: adding an Azure ML engineer to a cloud team.
Cloud and data engineering paired with AI/ML from an India-based bench. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Healthcare & life sciences, Retail & e-commerce, Logistics.
Decision matrix: EPAM Systems vs Simform
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; EPAM Systems rates higher overall |
| You want the supplier to own delivery as well as staffing | Both; EPAM Systems rates higher overall |
| You need one expert part-time | Neither lists part-time experts; ask about reduced hours |
| You want to test an engineer before signing for months | Neither publishes a trial; ask for a short first term |
| Your budget is at the lower end | Compare: EPAM Systems (Not published) vs Simform (Not published) |
| You need overlap with U.S. working hours | Neither is nearshore; agree overlap hours up front |
| You need specialist depth in a specific vertical | EPAM Systems |
Use case fit: EPAM Systems vs Simform
| Use case | EPAM Systems fit | Simform fit | Winner |
|---|---|---|---|
| Adding a 15-person GenAI squad to a bank's existing platform team | Strong | Strong | Both equally |
| Rolling out agentic workflows across several business units under one master agreement | Strong | Limited | EPAM Systems |
| Adding an Azure ML engineer to a cloud team | Strong | Strong | Both equally |
| Staffing data engineers for a SaaS analytics feature | Limited | Strong | Simform |
Verdict: EPAM Systems vs Simform
EPAM Systems (4.6/5) is the stronger overall choice for most AI Staff Augmentation projects. Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes.
Simform (3.8/5) is worth a look if you need staffing data engineers for a SaaS analytics feature. If your situation matches that, Simform is a competitive option.
Related comparisons
EPAM Systems vs Simform FAQ
Is EPAM Systems better than Simform?
EPAM Systems (4.6/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: a Q2 2026 earnings call put its Anthropic-certified engineer count above 5,700, the largest verified GenAI bench on this list. Simform's strongest advantage: cloud and data skills support production AI.
How do EPAM Systems and Simform differ in pricing?
EPAM Systems uses time and materials for augmented engineers; dedicated team and managed program contracts; rates on request pricing. Simform uses 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: EPAM Systems or Simform?
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 company before shortlisting.
What are the main differences between EPAM Systems and Simform?
EPAM Systems's primary differentiator is: thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes. Simform's primary differentiator is: cloud and data engineering paired with AI/ML from an India-based bench. They also differ in team size (61,000+ vs 1,000+), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Healthcare & life sciences vs Software & SaaS, Healthcare & life sciences).
Verify all details directly with each company before making a decision.