Best ML Development Services

EPAM Systems vs SoftServe: full comparison for 2026

Last updated: July 2026

Quick verdict

EPAM Systems (4.0/5) edges ahead of SoftServe (4.0/5) overall. EPAM Systems is the better choice for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner.. SoftServe is the stronger option for enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices.. The right choice depends on your project size, budget, and required tech stack.

EPAM Systems vs SoftServe: head-to-head summary

Criterion EPAM Systems SoftServe
Founded 1993 1993
HQ Newtown, Pennsylvania, United States Austin, Texas, United States / Lviv, Ukraine
Team size 50,000+ 12,000+
Rating 4.0 / 5 4.0 / 5
Best for Large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner. Enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices.
Pricing model Time & materials, managed engagement Time & materials, managed engagement
Min. engagement $100,000+ Not published
Primary tech stack AWS SageMaker, Azure ML, Databricks AWS, Azure, Google Cloud
Industries served FinTech, Healthcare, Retail & E-commerce, Manufacturing, Telecom Healthcare, FinTech, Retail & E-commerce, Manufacturing, Energy

EPAM Systems vs SoftServe: overview

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.

SoftServe

SoftServe was founded in 1993 in Lviv, Ukraine and now operates with a US headquarters in Austin, Texas and a European headquarters in Lviv, employing more than 12,000 people across 58 offices in 14 countries (with one source citing roughly 10,336 as of a recent count). The company's offerings span digital engineering, data analytics, cloud services, AI, machine learning, and IoT, and it ranked seventh among more than 130 Western European companies in Clutch's 2019 software development category. Its scale and 30+ year history make it a large, generalist engineering firm with AI as one of several core practices.

Services and capabilities: EPAM Systems vs SoftServe

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

Tech stack comparison: EPAM Systems vs SoftServe

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

Pricing comparison: EPAM Systems vs SoftServe

Criterion EPAM Systems SoftServe
Minimum engagement $100,000+ Not published
Engagement models Managed engagement, Time & materials, Staff augmentation Managed engagement, Time & materials, Staff augmentation
Rate transparency Minimum disclosed Not public
Price tier Mid-market Mid-market

Target audience comparison: EPAM Systems vs SoftServe

Dimension EPAM Systems SoftServe
Best company size Startup to mid-market Startup to mid-market
Best industries FinTech, Healthcare, Retail & E-commerce Healthcare, FinTech, Retail & E-commerce
Best use cases 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. Large enterprise wants a single vendor covering AI/ML alongside cloud, data analytics, and IoT services., Company needs a choice between US and EU contracting jurisdictions from the same firm.
Typical project type Managed engagement Managed engagement

EPAM Systems vs SoftServe: pros and cons

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.
SoftServe
+ 12,000+ employees across 58 offices in 14 countries gives it enterprise-scale delivery capacity and geographic redundancy.
+ 31 years of continuous operation (since 1993) through multiple technology cycles, including the post-2022 relocation pressures on Ukraine-founded firms.
+ Ranked 7th among 130+ Western European companies in Clutch's 2019 software development category, an independently sourced recognition.
+ Dual US/Ukraine headquarters structure gives clients a choice of contracting jurisdiction.
- 12,000+ person scale means AI/ML is one of several mature practices (alongside cloud, data analytics, IoT) rather than the firm's core identity.
- Reported employee counts vary by thousands across sources (10,336 vs. 12,000+), reflecting the difficulty of pinning down exact current headcount at this scale.

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.

Who should choose SoftServe?

SoftServe is the right choice for enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices..

31 years of engineering history (since 1993) with dual US and Ukraine headquarters and 12,000+ employees.. Minimum engagement starts at Not published. Works best with clients in Healthcare, FinTech, Retail & E-commerce, Manufacturing, Energy.

Decision matrix: EPAM Systems vs SoftServe

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: EPAM Systems ($100,000+) vs SoftServe (Not published)
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: EPAM Systems vs SoftServe

Use case EPAM Systems fit SoftServe fit Winner
Large enterprise with a $100K+ budget needs a publicly traded vendor for AI/ML procurement compliance requirements. Strong Strong Both equally
Fortune 500 company needs generative AI deployed at global scale with responsible-AI governance built in. Strong Limited EPAM Systems
Large enterprise wants a single vendor covering AI/ML alongside cloud, data analytics, and IoT services. Strong Strong Both equally
Company needs a choice between US and EU contracting jurisdictions from the same firm. Strong Strong Both equally
Fixed-scope ML build Limited Limited Both equally
Ongoing model retraining Limited Limited Both equally

Verdict: EPAM Systems vs SoftServe

EPAM Systems (4.0/5) is the stronger overall choice for most Machine Learning Development projects. Public-company (NYSE: EPAM) scale and compliance rigor, with 30+ years of engineering history predating the AI wave.. It is best for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner..

SoftServe (4.0/5) is the better choice when enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices.. If your situation matches those criteria, SoftServe is a competitive option.

Related comparisons

EPAM Systems vs SoftServe FAQ

Is EPAM Systems better than SoftServe?

EPAM Systems (4.0/5) scores higher overall, but "better" depends on your use case. EPAM Systems is better for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner.. SoftServe is better for enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices..

How do EPAM Systems and SoftServe differ in pricing?

EPAM Systems uses time & materials, managed engagement pricing with a minimum engagement of $100,000+. SoftServe uses time & materials, managed engagement 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: EPAM Systems or SoftServe?

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 EPAM Systems and SoftServe?

EPAM Systems's primary differentiator is: public-company (nyse: epam) scale and compliance rigor, with 30+ years of engineering history predating the ai wave.. SoftServe's primary differentiator is: 31 years of engineering history (since 1993) with dual us and ukraine headquarters and 12,000+ employees.. They also differ in team size (50,000+ vs 12,000+), minimum engagement ($100,000+ vs Not published), and primary industries served (FinTech, Healthcare vs Healthcare, FinTech).

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