Best ML Development Services

Yalantis vs EPAM Systems: full comparison for 2026

Last updated: July 2026

Quick verdict

Yalantis (4.0/5) edges ahead of EPAM Systems (4.0/5) overall. Yalantis is the better choice for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. EPAM Systems is the stronger option for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner.. The right choice depends on your project size, budget, and required tech stack.

Yalantis vs EPAM Systems: head-to-head summary

Criterion Yalantis EPAM Systems
Founded 2008 1993
HQ Larnaca, Cyprus Newtown, Pennsylvania, United States
Team size 500+ 50,000+
Rating 4.0 / 5 4.0 / 5
Best for Compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms. Large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner.
Pricing model Fixed project, dedicated team Time & materials, managed engagement
Min. engagement $10,000 $100,000+
Primary tech stack AWS SageMaker, Azure ML, Google Cloud Vertex AI AWS SageMaker, Azure ML, Databricks
Industries served Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain FinTech, Healthcare, Retail & E-commerce, Manufacturing, Telecom

Yalantis vs EPAM Systems: overview

Yalantis

Yalantis was founded in 2008 with headquarters in Larnaca, Cyprus and development hubs in Dnipro, Kyiv, and Lviv, Ukraine, growing to roughly 500 specialists. The firm positions itself as a 'compliance-first engineering partner,' building high-performance ML models across Amazon, Microsoft Azure, and Google Cloud ML platforms, including data preparation, model selection, training, deployment, and multimodal LLM processing for visual and text data. Project costs are reported to range from $10,000 to over $800,000, indicating the firm handles both small scoped projects and large enterprise programs.

EPAM Systems

EPAM Systems, Inc. (NYSE: EPAM) has operated since 1993 and has become one of the largest global digital transformation and engineering services providers, with a workforce in the tens of thousands. Its AI development services span generative AI, machine learning consulting, and intelligent automation, delivered by consultants, designers, and engineers who have worked with AI technologies for decades, and Clutch lists a minimum project size of $100,000+ with $150–$199/hr average rates. As a large publicly traded firm, EPAM offers the deepest compliance and financial transparency in this list, at a correspondingly higher entry price point.

Services and capabilities: Yalantis vs EPAM Systems

Capability Yalantis EPAM Systems
Custom ML Models
Computer Vision
NLP
MLOps
Generative AI
AI Consulting

Tech stack comparison: Yalantis vs EPAM Systems

Framework / platform Yalantis EPAM Systems
TensorFlow N/A N/A
PyTorch N/A N/A
AWS
Azure
Google Cloud N/A
LangChain N/A
Hugging Face N/A N/A
Kubernetes N/A

Pricing comparison: Yalantis vs EPAM Systems

Criterion Yalantis EPAM Systems
Minimum engagement $10,000 $100,000+
Engagement models Fixed project, Dedicated team, Staff augmentation Managed engagement, Time & materials, Staff augmentation
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Mid-market

Target audience comparison: Yalantis vs EPAM Systems

Dimension Yalantis EPAM Systems
Best company size Startup to mid-market Startup to mid-market
Best industries Healthcare, IoT & Embedded Systems, FinTech FinTech, Healthcare, Retail & E-commerce
Best use cases Healthcare or IoT company needs ML development from a compliance-first engineering partner., Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform. Large enterprise with a $100K+ budget needs a publicly traded vendor for AI/ML procurement compliance requirements., Fortune 500 company needs generative AI deployed at global scale with responsible-AI governance built in.
Typical project type Fixed project Managed engagement

Yalantis vs EPAM Systems: pros and cons

Yalantis
+ Compliance-first positioning is a genuine differentiator for regulated industries like healthcare and embedded/IoT systems.
+ Multi-cloud ML delivery capability (AWS, Azure, GCP) avoids vendor lock-in to a single hyperscaler.
+ Wide project-cost range ($10,000–$800,000+) means the firm can serve both small scoped projects and large programs without switching vendors.
+ 500+ specialists across three Ukrainian development hubs provides meaningful delivery redundancy.
- IoT and hardware engineering heritage means ML is one of several engineering disciplines rather than the firm's sole focus.
- Larnaca, Cyprus legal HQ with all technical delivery in Ukraine is standard for the region but worth confirming for contract jurisdiction purposes.
EPAM Systems
+ Publicly traded on the NYSE, giving clients access to audited financial disclosures unavailable from private competitors.
+ 50,000+ global workforce provides essentially unlimited delivery capacity for the largest enterprise AI programs.
+ 31+ years of engineering history (since 1993) predates the current AI hiring wave by decades.
+ AI/generative AI practice spans strategy through production deployment and responsible-AI compliance, covering the full enterprise lifecycle.
+ Scale/compliance standout among the researched companies — the clearest choice for regulated, large-budget enterprise programs.
- $100,000+ minimum project size (per Clutch) puts EPAM out of reach for startups and mid-market budgets under six figures.
- $150–$199/hr rate band is among the highest in this list, reflecting large-firm overhead.
- At 50,000+ employees, AI/ML is one practice among dozens — clients should confirm they're getting a dedicated AI pod, not a generalist team.

Who should choose Yalantis?

Yalantis is the right choice for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..

Compliance-first positioning combined with multi-cloud ML delivery (AWS, Azure, GCP) under one roof.. Minimum engagement starts at $10,000. Works best with clients in Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain.

Who should choose EPAM Systems?

EPAM Systems is the right choice for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner..

Public-company (NYSE: EPAM) scale and compliance rigor, with 30+ years of engineering history predating the AI wave.. Minimum engagement starts at $100,000+. Works best with clients in FinTech, Healthcare, Retail & E-commerce, Manufacturing, Telecom.

Decision matrix: Yalantis vs EPAM Systems

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Yalantis
You need a large dedicated team for an ongoing programme Yalantis
Your budget is at the lower end Yalantis
You need specialist depth in a specific vertical EPAM Systems
You need production MLOps support after model launch Both offer MLOps support
You need consulting before committing to a build EPAM Systems

Use case fit: Yalantis vs EPAM Systems

Use case Yalantis fit EPAM Systems fit Winner
Healthcare or IoT company needs ML development from a compliance-first engineering partner. Strong Strong Both equally
Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform. Strong Strong Both equally
Large enterprise with a $100K+ budget needs a publicly traded vendor for AI/ML procurement compliance requirements. Limited Strong EPAM Systems
Fortune 500 company needs generative AI deployed at global scale with responsible-AI governance built in. Limited Strong EPAM Systems
Fixed-scope ML build Limited Limited Both equally
Ongoing model retraining Limited Limited Both equally

Verdict: Yalantis vs EPAM Systems

Yalantis (4.0/5) is the stronger overall choice for most Machine Learning Development projects. Compliance-first positioning combined with multi-cloud ML delivery (AWS, Azure, GCP) under one roof.. It is best for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..

EPAM Systems (4.0/5) is the better choice when large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner.. If your situation matches those criteria, EPAM Systems is a competitive option.

Related comparisons

Yalantis vs EPAM Systems FAQ

Is Yalantis better than EPAM Systems?

Yalantis (4.0/5) scores higher overall, but "better" depends on your use case. Yalantis is better for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. EPAM Systems is better for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner..

How do Yalantis and EPAM Systems differ in pricing?

Yalantis uses fixed project, dedicated team pricing with a minimum engagement of $10,000. EPAM Systems uses time & materials, managed engagement pricing with a minimum engagement of $100,000+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Yalantis or EPAM Systems?

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 Yalantis and EPAM Systems?

Yalantis's primary differentiator is: compliance-first positioning combined with multi-cloud ml delivery (aws, azure, gcp) under one roof.. EPAM Systems's primary differentiator is: public-company (nyse: epam) scale and compliance rigor, with 30+ years of engineering history predating the ai wave.. They also differ in team size (500+ vs 50,000+), minimum engagement ($10,000 vs $100,000+), and primary industries served (Healthcare, IoT & Embedded Systems vs FinTech, Healthcare).

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