SoluLab vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
SoluLab (4.1/5) edges ahead of EPAM Systems (4.0/5) overall. SoluLab is the better choice for companies that want AI development from a vendor also fluent in blockchain/Web3 integration.. 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.
SoluLab vs EPAM Systems: head-to-head summary
| Criterion | SoluLab | EPAM Systems |
|---|---|---|
| Founded | 2014 | 1993 |
| HQ | Woodland Hills, California, United States | Newtown, Pennsylvania, United States |
| Team size | 246–250 | 50,000+ |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Best for | Companies that want AI development from a vendor also fluent in blockchain/Web3 integration. | Large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner. |
| Pricing model | Project-based, dedicated team | Time & materials, managed engagement |
| Min. engagement | Not published | $100,000+ |
| Primary tech stack | OpenAI API, LangChain, Python | AWS SageMaker, Azure ML, Databricks |
| Industries served | Media & Entertainment, Automotive, Education, FinTech | FinTech, Healthcare, Retail & E-commerce, Manufacturing, Telecom |
SoluLab vs EPAM Systems: overview
SoluLab
SoluLab was founded in 2014–2015 by Chintan Thakkar and Rajat Lala and is headquartered in Woodland Hills, California, with a team of roughly 246–250 engineers, data scientists, and AI specialists. The firm positions itself as an 'AI-native, Blockchain, and Web3' development company and reports having delivered 1,500+ projects across 15+ countries for clients including The Walt Disney Company, Mercedes-Benz, and the University of Cambridge (per company website; independently unverifiable at this scale). Its dual focus on AI and blockchain/Web3 makes it broader than a pure ML specialist.
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: SoluLab vs EPAM Systems
| Capability | SoluLab | EPAM Systems |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✓ |
Tech stack comparison: SoluLab vs EPAM Systems
| Framework / platform | SoluLab | EPAM Systems |
|---|---|---|
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: SoluLab vs EPAM Systems
| Criterion | SoluLab | EPAM Systems |
|---|---|---|
| Minimum engagement | Not published | $100,000+ |
| Engagement models | Project-based, Dedicated team | Managed engagement, Time & materials, Staff augmentation |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Mid-market |
Target audience comparison: SoluLab vs EPAM Systems
| Dimension | SoluLab | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Media & Entertainment, Automotive, Education | FinTech, Healthcare, Retail & E-commerce |
| Best use cases | Company building an AI product with a blockchain or Web3 component needs a single integrated vendor., Enterprise wants a vendor with named brand-name reference clients for procurement comfort. | 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 | Project-based | Managed engagement |
SoluLab vs EPAM Systems: pros and cons
| SoluLab | |
|---|---|
| + | Named enterprise clients (The Walt Disney Company, Mercedes-Benz, University of Cambridge) offer verifiable reference points, though the specific scope of each engagement is unconfirmed. |
| + | 246–250 team size supports mid-to-large engagements without enterprise-firm overhead. |
| + | Combined AI and blockchain/Web3 capability is useful for clients building tokenized or decentralized AI products. |
| + | 10 years of company history (since 2014–2015) under continuous founder leadership. |
| - | 1,500+ projects claim across 15+ countries is difficult to independently verify at face value. |
| - | Blockchain/Web3 focus alongside AI means clients purely interested in ML may be paying for adjacent expertise they don't need. |
| 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 SoluLab?
SoluLab is the right choice for companies that want AI development from a vendor also fluent in blockchain/Web3 integration..
Combines AI-native development with blockchain/Web3 expertise under one delivery team.. Minimum engagement starts at Not published. Works best with clients in Media & Entertainment, Automotive, Education, FinTech.
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: SoluLab vs EPAM Systems
| 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 | SoluLab |
| Your budget is at the lower end | Compare: SoluLab (Not published) vs EPAM Systems ($100,000+) |
| You need specialist depth in a specific vertical | EPAM Systems |
| You need production MLOps support after model launch | EPAM Systems |
| You need consulting before committing to a build | EPAM Systems |
Use case fit: SoluLab vs EPAM Systems
| Use case | SoluLab fit | EPAM Systems fit | Winner |
|---|---|---|---|
| Company building an AI product with a blockchain or Web3 component needs a single integrated vendor. | Strong | Strong | Both equally |
| Enterprise wants a vendor with named brand-name reference clients for procurement comfort. | 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: SoluLab vs EPAM Systems
SoluLab (4.1/5) is the stronger overall choice for most Machine Learning Development projects. Combines AI-native development with blockchain/Web3 expertise under one delivery team.. It is best for companies that want AI development from a vendor also fluent in blockchain/Web3 integration..
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
SoluLab vs EPAM Systems FAQ
Is SoluLab better than EPAM Systems?
SoluLab (4.1/5) scores higher overall, but "better" depends on your use case. SoluLab is better for companies that want AI development from a vendor also fluent in blockchain/Web3 integration.. EPAM Systems is better for large enterprises with $100K+ AI budgets that need a publicly traded, globally scaled engineering partner..
How do SoluLab and EPAM Systems differ in pricing?
SoluLab uses project-based, dedicated team pricing with a minimum engagement of Not published. 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: SoluLab or EPAM Systems?
SoluLab 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 SoluLab and EPAM Systems?
SoluLab's primary differentiator is: combines ai-native development with blockchain/web3 expertise under one delivery team.. 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 (246–250 vs 50,000+), minimum engagement (Not published vs $100,000+), and primary industries served (Media & Entertainment, Automotive vs FinTech, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.