Best Generative AI Development Services

SoftKraft vs EPAM Systems: full comparison for 2026

Quick verdict

EPAM Systems (4.1/5) edges ahead of SoftKraft (4.0/5) overall. EPAM Systems is the better choice for global enterprises running generative AI at massive scale. SoftKraft is the stronger option for startups on tight budgets needing generative AI MVPs. The right choice depends on your project size, budget, and required tech stack.

SoftKraft vs EPAM Systems: head-to-head summary

Criterion SoftKraft EPAM Systems
Founded 2015 1993
HQ Bielsko-Biala, Poland Newtown, United States
Team size 11-50 62,000+
Rating 4.0 / 5 4.1 / 5
Primary differentiator Small dedicated team priced for startup budgets, not enterprise rates Public-company scale (NYSE: EPAM) with financial transparency few competitors offer
Pricing model Fixed project or dedicated team Retainer or dedicated team, enterprise contracting
Min. engagement Not disclosed Not disclosed
Primary tech stack Python, OpenAI API, PostgreSQL Python, OpenAI API, AWS
Industries served Fintech, SaaS, Healthtech Financial services, Healthcare, Retail & e-commerce, Media & entertainment

SoftKraft vs EPAM Systems: overview

SoftKraft

SoftKraft was founded in 2015 by CEO Marek Petrykowski and CTO Blazej Kosmowski, running a lean 11-50 person team from Bielsko-Biala, Poland. Around 70% of its clients are North American despite the delivery team sitting in Poland. The firm's positioning centers on data-driven software and generative AI built specifically for startups and small-to-mid-sized companies, not enterprise accounts.

EPAM Systems

EPAM Systems dates to 1993, co-founded in New Jersey and Minsk by Arkadiy Dobkin and Leo Lozner, and has traded on the NYSE as an S&P 500 constituent since 2012. It employed roughly 62,850 people across more than 55 countries at the end of 2025, a scale category no other agency on this list approaches. Generative AI transformation engineering is a marketed practice area, but at this size it functions as part of a much larger digital engineering business rather than a standalone specialty.

Services and capabilities: SoftKraft vs EPAM Systems

Capability SoftKraft EPAM Systems
Generative AI
Machine learning
AI agents
MLOps
AI consulting
Fixed-price projects
Dedicated team model

Tech stack comparison: SoftKraft vs EPAM Systems

Framework / platform SoftKraft EPAM Systems
Python
OpenAI API
PyTorch N/A N/A
LangChain N/A N/A
AWS
Azure N/A
Kubernetes N/A N/A

Pricing comparison: SoftKraft vs EPAM Systems

Criterion SoftKraft EPAM Systems
Minimum engagement Not disclosed Not disclosed
Engagement models Fixed project, Dedicated team Dedicated team, Retainer
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: SoftKraft vs EPAM Systems

Dimension SoftKraft EPAM Systems
Best company size Startup to mid-market Startup to mid-market
Best industries Fintech, SaaS, Healthtech Financial services, Healthcare, Retail & e-commerce
Best use cases Building a generative AI-powered MVP for a pre-seed or seed-stage startup., Getting generative AI and data engineering handled by one small, accountable team. Running a generative AI transformation program spanning multiple business units and regions., Needing a publicly-traded vendor for audit or procurement compliance reasons.
Typical project type Fixed project Dedicated team

SoftKraft vs EPAM Systems: pros and cons

SoftKraft
+ Smaller team size keeps overhead, and likely cost, below mid-size and enterprise agencies.
+ 70% North American client base shows the team has adapted to US buyer expectations from Poland.
+ Founder-led leadership stays close to delivery rather than purely sales.
+ Startup and SME focus means scope and pricing fit smaller budgets from the outset.
- Team of 11-50 limits capacity to a handful of concurrent projects
- Less public case-study history than agencies with a decade-plus track record
EPAM Systems
+ Public-company financial disclosure that no private agency on this list can match.
+ Scale to staff several large generative AI programs across regions simultaneously.
+ S&P 500 membership lets enterprise procurement teams vet it through standard due diligence.
+ Partnerships span all three major cloud hyperscalers.
- Generative AI sits inside an enormous engineering business rather than as a dedicated specialty
- Scale generally means slower onboarding and higher minimum engagement than boutique firms

Who should choose SoftKraft?

A typical fit: building a generative AI-powered MVP for a pre-seed or seed-stage startup.

Small dedicated team priced for startup budgets, not enterprise rates. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, SaaS, Healthtech.

Who should choose EPAM Systems?

A typical fit: running a generative AI transformation program spanning multiple business units and regions.

Public-company scale (NYSE: EPAM) with financial transparency few competitors offer. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media & entertainment.

Decision matrix: SoftKraft vs EPAM Systems

Your situation Recommended choice
You need full-ownership delivery on a defined project scope SoftKraft
You need a large dedicated team for an ongoing programme SoftKraft
Your budget is at the lower end Compare: SoftKraft (Not disclosed) vs EPAM Systems (Not disclosed)
You need specialist depth in a specific vertical EPAM Systems
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build SoftKraft

Use case fit: SoftKraft vs EPAM Systems

Use case SoftKraft fit EPAM Systems fit Winner
Building a generative AI-powered MVP for a pre-seed or seed-stage startup. Strong Limited SoftKraft
Getting generative AI and data engineering handled by one small, accountable team. Strong Limited SoftKraft
Running a generative AI transformation program spanning multiple business units and regions. Limited Strong EPAM Systems
Needing a publicly-traded vendor for audit or procurement compliance reasons. Limited Strong EPAM Systems
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: SoftKraft vs EPAM Systems

EPAM Systems (4.1/5) is the stronger overall choice for most Generative AI Development projects. Public-company scale (NYSE: EPAM) with financial transparency few competitors offer.

SoftKraft (4.0/5) is worth a look if you need getting generative AI and data engineering handled by one small, accountable team. If your situation matches that, SoftKraft is a competitive option.

Related comparisons

SoftKraft vs EPAM Systems FAQ

Is SoftKraft better than EPAM Systems?

EPAM Systems (4.1/5) scores higher overall, but "better" depends on your use case. SoftKraft's strongest advantage: smaller team size keeps overhead, and likely cost, below mid-size and enterprise agencies. EPAM Systems's strongest advantage: public-company financial disclosure that no private agency on this list can match.

How do SoftKraft and EPAM Systems differ in pricing?

SoftKraft uses fixed project or dedicated team pricing. EPAM Systems uses retainer or dedicated team, enterprise contracting pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: SoftKraft 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 SoftKraft and EPAM Systems?

SoftKraft's primary differentiator is: small dedicated team priced for startup budgets, not enterprise rates. EPAM Systems's primary differentiator is: public-company scale (NYSE: EPAM) with financial transparency few competitors offer. They also differ in team size (11-50 vs 62,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Fintech, SaaS vs Financial services, Healthcare).

Verify all details directly with each company before making a decision.