Scopic vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
Scopic (3.8/5) edges ahead of EPAM Systems (3.5/5) overall. Scopic is the better choice for companies needing senior ML engineers at competitive rates with distributed team flexibility and published case studies across multiple industries. 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.
Scopic vs EPAM Systems: head-to-head summary
| Criterion | Scopic | EPAM Systems |
|---|---|---|
| Founded | 2006 | 1993 |
| HQ | Marlborough, MA, USA (distributed) | Newtown, PA, USA |
| Team size | 1,000–2,000 | 60,000+ |
| Rating | 3.8 / 5 | 3.5 / 5 |
| Best for | Companies needing senior ML engineers at competitive rates with distributed team flexibility and published case studies across multiple industries | Large enterprises needing ML within large-scale platform engineering programmes and access to a proprietary AI orchestration platform |
| Pricing model | Dedicated team, T&M, fixed project | Dedicated team, T&M |
| Min. engagement | $30K | $200K+ |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, EPAM DIAL, AWS |
| Industries served | Healthcare, Manufacturing, Fintech, Logistics, SaaS | Fintech, Healthcare, Manufacturing, SaaS, Logistics |
Scopic vs EPAM Systems: overview
Scopic
Scopic is a globally distributed software development company headquartered in Marlborough, Massachusetts, with a remote-first team of 1,000+ engineers spanning 50+ countries. Founded in 2006, Scopic builds custom ML systems using TensorFlow, neural networks, and PyTorch for clients in transportation, healthcare, manufacturing, and finance. The distributed model keeps overhead low while providing senior engineering talent across multiple time zones. Scopic has published ML case studies in medical imaging, predictive maintenance, and financial risk modelling.
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: Scopic vs EPAM Systems
| Capability | Scopic | 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: Scopic vs EPAM Systems
| Framework / platform | Scopic | EPAM Systems |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | ✓ |
| Scikit-learn | ✓ | N/A |
| AWS SageMaker | N/A | N/A |
| MLflow | N/A | ✓ |
| Hugging Face | N/A | N/A |
| LangChain | N/A | N/A |
| Docker/Kubernetes | N/A | N/A |
| Databricks | N/A | ✓ |
Pricing comparison: Scopic vs EPAM Systems
| Criterion | Scopic | EPAM Systems |
|---|---|---|
| Minimum engagement | $30K | $200K+ |
| Engagement models | Dedicated team, Time & materials, Fixed project | Dedicated team, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Scopic vs EPAM Systems
| Dimension | Scopic | EPAM Systems |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Healthcare, Manufacturing, Fintech | Fintech, Healthcare, Manufacturing |
| Best use cases | Medical imaging analysis using CNN-based deep learning models, Predictive maintenance systems for manufacturing equipment | Enterprise AI transformation programmes for Fortune 500 organisations, EPAM DIAL deployment for enterprise LLM governance and AI orchestration |
| Typical project type | Dedicated team | Dedicated team |
Scopic vs EPAM Systems: pros and cons
| Scopic | |
|---|---|
| + | 20-year track record with 1,000+ distributed engineers provides delivery confidence |
| + | Published ML case studies in healthcare imaging, manufacturing maintenance, and financial risk |
| + | Remote-first model provides access to senior talent at competitive rates |
| + | Wide range of ML use cases covered across multiple industries |
| + | Flexible engagement: dedicated team, T&M, or fixed project scope |
| - | Fully distributed model requires strong async communication discipline from client teams |
| - | ML is one of several practice areas — not a pure-play AI specialist firm |
| - | Less emphasis on cutting-edge deep learning research than boutique ML-only firms |
| 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 Scopic?
Scopic is the right choice for companies needing senior ML engineers at competitive rates with distributed team flexibility and published case studies across multiple industries.
20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk. Minimum engagement starts at $30K. Works best with clients in Healthcare, Manufacturing, Fintech, Logistics, SaaS.
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: Scopic vs EPAM Systems
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Scopic |
| You need a large dedicated team for an ongoing programme | Scopic |
| Your budget is at the lower end | Scopic |
| You need specialist depth in a specific vertical | Scopic |
| 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: Scopic vs EPAM Systems
| Use case | Scopic fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Medical imaging analysis using CNN-based deep learning models | Strong | Limited | Scopic |
| Predictive maintenance systems for manufacturing equipment | Strong | Limited | Scopic |
| 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: Scopic vs EPAM Systems
Scopic (3.8/5) is the stronger overall choice for most Machine Learning Development projects. 20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk. It is best for companies needing senior ML engineers at competitive rates with distributed team flexibility and published case studies across multiple industries.
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
Scopic vs EPAM Systems FAQ
Is Scopic better than EPAM Systems?
Scopic (3.8/5) scores higher overall, but "better" depends on your use case. Scopic is better for companies needing senior ML engineers at competitive rates with distributed team flexibility and published case studies across multiple industries. 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 Scopic and EPAM Systems differ in pricing?
Scopic uses dedicated team, t&m, fixed project pricing with a minimum engagement of $30K. 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: Scopic or EPAM Systems?
Scopic 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 Scopic and EPAM Systems?
Scopic's primary differentiator is: 20-year distributed firm with 1,000+ remote engineers and published ml case studies in healthcare, manufacturing, and financial risk. 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 (1,000–2,000 vs 60,000+), minimum engagement ($30K vs $200K+), and primary industries served (Healthcare, Manufacturing vs Fintech, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.