Best Machine Learning Development Companies

Scopic vs EPAM Systems: full comparison for 2026

Last updated: July 2026

Quick verdict

Scopic (3.9/5) edges ahead of EPAM Systems (3.9/5) overall. Scopic is the better choice for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability. EPAM Systems is the stronger option for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration. 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 Newtown, PA, USA
Team size 250–500 62,000+
Rating 3.9 / 5 3.9 / 5
Best for Organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability Large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration
Pricing model Fixed project, T&M, Dedicated team Dedicated team, T&M, Fixed project, Staff augmentation
Min. engagement $20K $50K
Primary tech stack TensorFlow, PyTorch, Keras Python, TensorFlow, PyTorch
Industries served transportation, healthcare, manufacturing, financial services, edtech financial services, healthcare, retail, media, government

Scopic vs EPAM Systems: overview

Scopic

Scopic is a globally distributed software development company founded in 2006 and headquartered in Marlborough, Massachusetts. The company employs 250–500 professionals and has 20 years of experience building custom ML systems using TensorFlow, neural networks, PyTorch, and computer vision pipelines. Scopic has confirmed production ML deployments across transportation, healthcare, manufacturing, and financial services.

EPAM Systems

EPAM Systems is a global technology engineering company founded in 1993 and headquartered in Newtown, Pennsylvania. The company employs 62,000+ engineers across 50+ countries and is publicly traded on the NYSE. EPAM provides end-to-end AI development services from strategy and consulting to implementation and support, working with Fortune 500 clients across financial services, healthcare, retail, media, and government. EPAM is the largest firm in this review, with AI/ML capabilities delivered within a full-service technology engineering operation.

Services and capabilities: Scopic vs EPAM Systems

Capability Scopic EPAM Systems
Custom ML development
ML consulting
Deep learning
NLP
Computer vision
MLOps
Predictive analytics
Generative AI
Data engineering
Staff augmentation

Tech stack comparison: Scopic vs EPAM Systems

Framework / platform Scopic EPAM Systems
TensorFlow
PyTorch
Scikit-Learn N/A
LangChain N/A N/A
AWS SageMaker N/A
Azure ML N/A
GCP Vertex AI N/A N/A
Kubernetes N/A
Apache Spark N/A
MLflow N/A

Pricing comparison: Scopic vs EPAM Systems

Criterion Scopic EPAM Systems
Minimum engagement $20K $50K
Engagement models Fixed project, T&M, Dedicated team Dedicated team, T&M, Fixed project, Staff augmentation
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: Scopic vs EPAM Systems

Dimension Scopic EPAM Systems
Best company size Startup to mid-market Startup to mid-market
Best industries transportation, healthcare, manufacturing financial services, healthcare, retail
Best use cases Custom computer vision pipeline development for transportation safety or logistics automation, Deep learning model development for medical image analysis or clinical data classification Global enterprise AI transformation programme requiring multi-country deployment and governance, Complex Fortune 500 ML programme integrating across dozens of legacy systems
Typical project type Fixed project Dedicated team

Scopic vs EPAM Systems: pros and cons

Scopic
+ 20 years of distributed ML delivery with consistent process maturity across time zones
+ Deep computer vision and neural network expertise with production deployments in transportation
+ Custom ML system engineering — not platform-reliant solutions dependent on third-party services
+ Accessible minimum engagement and competitive rates for the level of specialization offered
+ Healthcare ML experience with sensitivity to data privacy and regulatory considerations
- Distributed-first model may introduce coordination overhead for clients preferring on-site collaboration
- Less public brand presence than US-headquartered firms of similar capability
- Less generative AI and LLM tooling depth than newer AI-first firms
EPAM Systems
+ 62,000+ engineers provides unmatched scale for simultaneous large-scale enterprise ML programmes
+ Publicly traded NYSE company with audited financials — maximum organizational stability and governance
+ Global delivery across 50+ countries enables ML delivery under local data sovereignty requirements
+ Full AI lifecycle from strategy through production MLOps within one organizational relationship
+ Fortune 500 client base validates enterprise-grade ML delivery at the highest complexity level
- Enterprise scale means ML projects go through larger organizational process — slower initiation than boutiques
- High minimum engagement ($50K) limits accessibility for SMBs or early-stage organizations
- Generalist technology engineering scope means ML specialist depth may be lower per individual than pure-play ML boutiques

Who should choose Scopic?

Scopic is the right choice for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability.

20+ years as a distributed software company gives Scopic strong custom ML engineering discipline with confirmed production deployments across transportation and healthcare. Minimum engagement starts at $20K. Works best with clients in transportation, healthcare, manufacturing, financial services, edtech.

Who should choose EPAM Systems?

EPAM Systems is the right choice for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.

62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes. Minimum engagement starts at $50K. Works best with clients in financial services, healthcare, retail, media, government.

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 EPAM Systems
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
Custom computer vision pipeline development for transportation safety or logistics automation Strong Limited Scopic
Deep learning model development for medical image analysis or clinical data classification Strong Limited Scopic
Global enterprise AI transformation programme requiring multi-country deployment and governance Limited Strong EPAM Systems
Complex Fortune 500 ML programme integrating across dozens of legacy systems Limited Strong EPAM Systems
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Scopic vs EPAM Systems

Scopic (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 20+ years as a distributed software company gives Scopic strong custom ML engineering discipline with confirmed production deployments across transportation and healthcare. It is best for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability.

EPAM Systems (3.9/5) is the better choice when large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration. 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 (3.9/5) scores higher overall, but "better" depends on your use case. Scopic is better for organizations needing fully custom ML engineering with 20+ years of distributed team experience and strong computer vision and deep learning capability. EPAM Systems is better for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.

How do Scopic and EPAM Systems differ in pricing?

Scopic uses fixed project, t&m, dedicated team pricing with a minimum engagement of $20K. EPAM Systems uses dedicated team, t&m, fixed project, staff augmentation pricing with a minimum engagement of $50K. 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+ years as a distributed software company gives scopic strong custom ml engineering discipline with confirmed production deployments across transportation and healthcare. EPAM Systems's primary differentiator is: 62,000+ engineers across 50+ countries delivering ml inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise ai programmes. They also differ in team size (250–500 vs 62,000+), minimum engagement ($20K vs $50K), and primary industries served (transportation, healthcare vs financial services, healthcare).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.