Persistent Systems vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
Persistent Systems (3.9/5) edges ahead of EPAM Systems (3.9/5) overall. Persistent Systems is the better choice for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators.. EPAM Systems is the stronger option for very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform.. The right choice depends on your project size, budget, and required tech stack.
Persistent Systems vs EPAM Systems: head-to-head summary
| Criterion | Persistent Systems | EPAM Systems |
|---|---|---|
| Founded | 1990 | 1993 |
| HQ | Pune, India | Newtown, USA |
| Team size | 10,000+ | 10,000+ |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Best for | Mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators. | Very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform. |
| Pricing model | Not published; enterprise project engagements | Not published; enterprise project engagements |
| Min. engagement | Not published | Not published |
| Primary tech stack | AWS, Microsoft Azure, Google Cloud | AWS SageMaker, Amazon Bedrock, EPAM DIAL (proprietary) |
| Industries served | Healthcare, Financial services, Technology/software, Life sciences | Financial services, Life sciences, Media, Travel and hospitality |
Persistent Systems vs EPAM Systems: overview
Persistent Systems
Persistent Systems Limited was founded in 1990 in Pune, India, by Dr. Anand Deshpande, and has grown into a publicly traded (NSE/BSE: PERSISTENT) multinational technology services company with more than 24,000 employees. Its Data Science and Machine Learning practice spans data engineering through enterprise ML deployment across AWS, Azure, and Google Cloud, supported by its Data Experience Hub (DxH), a set of accelerators aimed at operationalizing ML and detecting bias in models through explainable AI. Persistent was named a Leader in the Everest Group Data & AI PEAK Matrix 2025 for the mid-market segment, and holds AWS Premier Tier Partner and Google Cloud Data & Analytics plus Machine Learning Specializations.
EPAM Systems
EPAM Systems was founded in 1993 in Newtown, Pennsylvania by Arkadiy Dobkin and Leo Lozner, and has grown into a publicly traded (NYSE: EPAM) global engineering company with more than 53,000 employees. EPAM's AI/ML practice includes model development and deployment on Amazon SageMaker and Amazon Bedrock, MLOps, and its proprietary DIAL platform, an enterprise AI orchestration layer. The company was named AWS Global Innovation Partner of the Year in 2025 and holds AWS Premier Tier Services Partner status, reflecting deep hyperscaler-certified delivery capability at very large scale.
Services and capabilities: Persistent Systems vs EPAM Systems
| Capability | Persistent Systems | EPAM Systems |
|---|---|---|
| Custom model training | ✓ | ✓ |
| Fine-tuning & adaptation | ✗ | ✗ |
| MLOps pipeline | ✓ | ✓ |
| Model deployment & serving | ✗ | ✓ |
| Data engineering for ML | ✓ | ✗ |
| ML infrastructure management | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP & LLM development | ✗ | ✗ |
| Forecasting & time-series modeling | ✗ | ✗ |
| ML strategy consulting | ✗ | ✗ |
Tech stack comparison: Persistent Systems vs EPAM Systems
| Framework / platform | Persistent Systems | EPAM Systems |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | ✓ |
| Amazon Bedrock | N/A | ✓ |
| Google Cloud | ✓ | N/A |
| Microsoft Azure | ✓ | N/A |
| Kubernetes | N/A | ✓ |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: Persistent Systems vs EPAM Systems
| Criterion | Persistent Systems | EPAM Systems |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Enterprise project engagement, Managed AI services | Enterprise project engagement, Managed AI services |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Persistent Systems vs EPAM Systems
| Dimension | Persistent Systems | EPAM Systems |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Healthcare, Financial services, Technology/software | Financial services, Life sciences, Media |
| Best use cases | Operationalizing ML models at enterprise scale using pre-built MLOps accelerators, Running bias detection and explainable AI reviews on existing production models | Very large enterprises needing an AWS Global Partner of the Year-caliber vendor for ML platform work, Deploying models on Amazon SageMaker or Bedrock with EPAM's proprietary DIAL orchestration layer |
| Typical project type | Enterprise project engagement | Enterprise project engagement |
Persistent Systems vs EPAM Systems: pros and cons
| Persistent Systems | |
|---|---|
| + | Everest Group Leader ranking in the Data & AI PEAK Matrix 2025 (mid-market segment) is an independently sourced third-party validation. |
| + | Purpose-built DxH accelerators for MLOps and bias detection add concrete, named tooling beyond generic claims. |
| + | Publicly traded with 35-year operating history, providing financial transparency. |
| + | Named healthcare client work (e.g., cancer-detection collaboration) with a specific, checkable use case. |
| - | Very large scale (24,000+ employees) means ML/AI is one of several major practice areas competing for delivery focus. |
| - | No clearly located aggregate Clutch/G2 star rating specific to its AI practice in available public sources. |
| - | Pricing model and minimum engagement are not published. |
| - | India-centric delivery model may require additional coordination for clients preferring more localized teams. |
| EPAM Systems | |
|---|---|
| + | 2025 AWS Global Innovation Partner of the Year, an independently awarded distinction from AWS itself. |
| + | Proprietary DIAL orchestration platform provides a differentiated technical asset beyond standard consulting delivery. |
| + | Publicly traded (NYSE: EPAM) with substantial financial transparency and scale (53,000+ employees). |
| + | AWS Premier Tier Services Partner status confirms deep, audited hyperscaler certification. |
| - | Very large, generalist software engineering brand means ML/AI is one of many practice areas, not a dedicated specialization. |
| - | No clearly located aggregate Clutch/G2 star rating specific to its AI practice in available public sources. |
| - | Pricing model and minimum engagement are not published, and enterprise minimums are typically substantial. |
| - | Named client-specific ML case studies were not clearly surfaced in available search results. |
Who should choose Persistent Systems?
Persistent Systems is the right choice for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators..
Purpose-built DxH accelerator suite for MLOps and bias detection, plus a specific Everest Group Leader ranking in the mid-market Data & AI segment rather than only the largest enterprise tier.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Financial services, Technology/software, Life sciences.
Who should choose EPAM Systems?
EPAM Systems is the right choice for very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform..
Proprietary EPAM DIAL platform for enterprise AI orchestration, combined with the 2025 AWS Global Innovation Partner of the Year distinction, an award-level differentiator not held by most peers.. Minimum engagement starts at Not published. Works best with clients in Financial services, Life sciences, Media, Travel and hospitality.
Decision matrix: Persistent Systems 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 | Check each company's engagement model |
| Your budget is at the lower end | Compare: Persistent Systems (Not published) vs EPAM Systems (Not published) |
| You need specialist depth in a specific vertical | Persistent 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: Persistent Systems vs EPAM Systems
| Use case | Persistent Systems fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Operationalizing ML models at enterprise scale using pre-built MLOps accelerators | Strong | Limited | Persistent Systems |
| Running bias detection and explainable AI reviews on existing production models | Strong | Strong | Both equally |
| Very large enterprises needing an AWS Global Partner of the Year-caliber vendor for ML platform work | Limited | Strong | EPAM Systems |
| Deploying models on Amazon SageMaker or Bedrock with EPAM's proprietary DIAL orchestration layer | Limited | Strong | EPAM Systems |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Strong | Both equally |
Verdict: Persistent Systems vs EPAM Systems
Persistent Systems (3.9/5) is the stronger overall choice for most ML Model Development projects. Purpose-built DxH accelerator suite for MLOps and bias detection, plus a specific Everest Group Leader ranking in the mid-market Data & AI segment rather than only the largest enterprise tier.. It is best for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators..
EPAM Systems (3.9/5) is the better choice when very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform.. If your situation matches those criteria, EPAM Systems is a competitive option.
Related comparisons
Persistent Systems vs EPAM Systems FAQ
Is Persistent Systems better than EPAM Systems?
Persistent Systems (3.9/5) scores higher overall, but "better" depends on your use case. Persistent Systems is better for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators.. EPAM Systems is better for very large enterprises wanting a publicly traded, AWS Global Partner of the Year-caliber vendor with a proprietary AI orchestration platform..
How do Persistent Systems and EPAM Systems differ in pricing?
Persistent Systems uses not published; enterprise project engagements pricing with a minimum engagement of Not published. EPAM Systems uses not published; enterprise project engagements pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Persistent Systems or EPAM Systems?
Persistent 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 Persistent Systems and EPAM Systems?
Persistent Systems's primary differentiator is: purpose-built dxh accelerator suite for mlops and bias detection, plus a specific everest group leader ranking in the mid-market data & ai segment rather than only the largest enterprise tier.. EPAM Systems's primary differentiator is: proprietary epam dial platform for enterprise ai orchestration, combined with the 2025 aws global innovation partner of the year distinction, an award-level differentiator not held by most peers.. They also differ in team size (10,000+ vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Financial services vs Financial services, Life sciences).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.