ScienceSoft vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
ScienceSoft (3.9/5) edges ahead of EPAM Systems (3.5/5) overall. ScienceSoft is the better choice for manufacturing, healthcare, and oil & gas companies needing a long-established US-headquartered ML partner with Microsoft and AWS credentials. EPAM Systems is the stronger option for large enterprises needing ML within large-scale platform engineering programmes and access to a proprietary AI orchestration platform. The right choice depends on your project size, budget, and required tech stack.
ScienceSoft vs EPAM Systems: head-to-head summary
| Criterion | ScienceSoft | EPAM Systems |
|---|---|---|
| Founded | 1989 | 1993 |
| HQ | McKinney, TX, USA | Newtown, PA, USA |
| Team size | 700–1,000 | 60,000+ |
| Rating | 3.9 / 5 | 3.5 / 5 |
| Best for | Manufacturing, healthcare, and oil & gas companies needing a long-established US-headquartered ML partner with Microsoft and AWS credentials | Large enterprises needing ML within large-scale platform engineering programmes and access to a proprietary AI orchestration platform |
| Pricing model | Fixed project, dedicated team, T&M | Dedicated team, T&M |
| Min. engagement | $50K | $200K+ |
| Primary tech stack | Python, Scikit-learn, TensorFlow | Python, EPAM DIAL, AWS |
| Industries served | Manufacturing, Healthcare, SaaS, Logistics, Fintech | Fintech, Healthcare, Manufacturing, SaaS, Logistics |
ScienceSoft vs EPAM Systems: overview
ScienceSoft
ScienceSoft is a global IT services company founded in 1989 and headquartered in McKinney, Texas, with 700+ employees and delivery centres in Eastern Europe and the Americas. The firm's machine learning practice focuses on custom ML solutions for manufacturing, healthcare, and oil & gas industries, with a 35-year IT track record across 20+ countries. ScienceSoft's ML engineers design and implement models for demand forecasting, quality prediction, medical diagnostics, and production optimisation. The company holds Microsoft Gold Partnership and AWS Partner certifications.
EPAM Systems
EPAM Systems is a global software engineering and digital services company founded in 1993 and headquartered in Newtown, Pennsylvania, publicly listed on the NYSE with 62,000+ professionals across 55+ countries. The company's AI and ML services encompass data engineering, platform modernisation, advanced analytics, and AI/ML model development, alongside its proprietary EPAM DIAL enterprise AI orchestration platform. EPAM has positioned itself as a leader in AI transformation engineering, integrating ML capability within large digital product and platform engineering programmes.
Services and capabilities: ScienceSoft vs EPAM Systems
| Capability | ScienceSoft | EPAM Systems |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP & text analytics | ✗ | ✗ |
| MLOps & deployment | ✓ | ✓ |
| Generative AI | ✗ | ✓ |
| ML consulting & strategy | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: ScienceSoft vs EPAM Systems
| Framework / platform | ScienceSoft | EPAM Systems |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | ✓ |
| Scikit-learn | ✓ | N/A |
| AWS SageMaker | ✓ | N/A |
| MLflow | ✓ | ✓ |
| Hugging Face | N/A | N/A |
| LangChain | N/A | N/A |
| Docker/Kubernetes | N/A | N/A |
| Databricks | N/A | ✓ |
Pricing comparison: ScienceSoft vs EPAM Systems
| Criterion | ScienceSoft | EPAM Systems |
|---|---|---|
| Minimum engagement | $50K | $200K+ |
| Engagement models | Fixed project, Dedicated team, Time & materials | Dedicated team, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: ScienceSoft vs EPAM Systems
| Dimension | ScienceSoft | EPAM Systems |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Manufacturing, Healthcare, SaaS | Fintech, Healthcare, Manufacturing |
| Best use cases | Demand forecasting and production optimisation ML for manufacturing plants, Clinical decision support ML for healthcare providers and hospital systems | Enterprise AI transformation programmes for Fortune 500 organisations, EPAM DIAL deployment for enterprise LLM governance and AI orchestration |
| Typical project type | Fixed project | Dedicated team |
ScienceSoft vs EPAM Systems: pros and cons
| ScienceSoft | |
|---|---|
| + | 35-year delivery track record provides confidence for regulated industry procurement requirements |
| + | Microsoft Gold and AWS Partner certifications verify cloud ML deployment credentials |
| + | Deep manufacturing, healthcare, and oil & gas ML vertical expertise with named case studies |
| + | 700+ employees provide delivery capacity for large concurrent enterprise programmes |
| + | US Texas HQ for North American enterprise client engagement and account management |
| - | ML is one of many IT service lines — not a pure-play AI specialist firm |
| - | Primary vertical focus on manufacturing and healthcare may not serve other sectors equally well |
| - | Higher minimum engagement than boutique ML alternatives at similar quality tier |
| EPAM Systems | |
|---|---|
| + | Publicly listed company provides financial transparency and governance confidence |
| + | 62,000+ engineers deliver at a scale few ML development competitors can match |
| + | Proprietary EPAM DIAL AI orchestration platform for enterprise LLM management |
| + | AI transformation engineering positioning beyond standard ML delivery |
| + | 55+ country footprint supports global enterprise programme delivery and compliance |
| - | Very high minimum engagement ($200K+) limits access to large enterprise budgets |
| - | ML is one capability within a massive engineering conglomerate — specialist depth varies by practice and team |
| - | Eastern European primary delivery requires business continuity planning for regulated clients |
Who should choose ScienceSoft?
ScienceSoft is the right choice for manufacturing, healthcare, and oil & gas companies needing a long-established US-headquartered ML partner with Microsoft and AWS credentials.
35-year IT firm with Microsoft Gold and AWS partner certifications and documented vertical depth in manufacturing, healthcare, and oil & gas ML. Minimum engagement starts at $50K. Works best with clients in Manufacturing, Healthcare, SaaS, Logistics, Fintech.
Who should choose EPAM Systems?
EPAM Systems is the right choice for large enterprises needing ML within large-scale platform engineering programmes and access to a proprietary AI orchestration platform.
Publicly traded 62,000-person firm with proprietary EPAM DIAL AI orchestration platform and AI transformation engineering positioning for global enterprises. Minimum engagement starts at $200K+. Works best with clients in Fintech, Healthcare, Manufacturing, SaaS, Logistics.
Decision matrix: ScienceSoft vs EPAM Systems
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | ScienceSoft |
| You need a large dedicated team for an ongoing programme | ScienceSoft |
| Your budget is at the lower end | ScienceSoft |
| You need specialist depth in a specific vertical | ScienceSoft |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | ScienceSoft |
Use case fit: ScienceSoft vs EPAM Systems
| Use case | ScienceSoft fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Demand forecasting and production optimisation ML for manufacturing plants | Strong | Limited | ScienceSoft |
| Clinical decision support ML for healthcare providers and hospital systems | Strong | Limited | ScienceSoft |
| Enterprise AI transformation programmes for Fortune 500 organisations | Limited | Strong | EPAM Systems |
| EPAM DIAL deployment for enterprise LLM governance and AI orchestration | Limited | Strong | EPAM Systems |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: ScienceSoft vs EPAM Systems
ScienceSoft (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 35-year IT firm with Microsoft Gold and AWS partner certifications and documented vertical depth in manufacturing, healthcare, and oil & gas ML. It is best for manufacturing, healthcare, and oil & gas companies needing a long-established US-headquartered ML partner with Microsoft and AWS credentials.
EPAM Systems (3.5/5) is the better choice when large enterprises needing ML within large-scale platform engineering programmes and access to a proprietary AI orchestration platform. If your situation matches those criteria, EPAM Systems is a competitive option.
Related comparisons
ScienceSoft vs EPAM Systems FAQ
Is ScienceSoft better than EPAM Systems?
ScienceSoft (3.9/5) scores higher overall, but "better" depends on your use case. ScienceSoft is better for manufacturing, healthcare, and oil & gas companies needing a long-established US-headquartered ML partner with Microsoft and AWS credentials. EPAM Systems is better for large enterprises needing ML within large-scale platform engineering programmes and access to a proprietary AI orchestration platform.
How do ScienceSoft and EPAM Systems differ in pricing?
ScienceSoft uses fixed project, dedicated team, t&m pricing with a minimum engagement of $50K. EPAM Systems uses dedicated team, t&m pricing with a minimum engagement of $200K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: ScienceSoft or EPAM Systems?
ScienceSoft 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 ScienceSoft and EPAM Systems?
ScienceSoft's primary differentiator is: 35-year it firm with microsoft gold and aws partner certifications and documented vertical depth in manufacturing, healthcare, and oil & gas ml. EPAM Systems's primary differentiator is: publicly traded 62,000-person firm with proprietary epam dial ai orchestration platform and ai transformation engineering positioning for global enterprises. They also differ in team size (700–1,000 vs 60,000+), minimum engagement ($50K vs $200K+), and primary industries served (Manufacturing, Healthcare vs Fintech, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.