Miquido vs EPAM Systems: full comparison for 2026
Last updated: July 2026
Quick verdict
Miquido (4.0/5) edges ahead of EPAM Systems (3.9/5) overall. Miquido is the better choice for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise. 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.
Miquido vs EPAM Systems: head-to-head summary
| Criterion | Miquido | EPAM Systems |
|---|---|---|
| Founded | 2011 | 1993 |
| HQ | Krakow, Poland | Newtown, PA, USA |
| Team size | 150–300 | 62,000+ |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Best for | Product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise | Large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration |
| Pricing model | Fixed project, Dedicated team, T&M | Dedicated team, T&M, Fixed project, Staff augmentation |
| Min. engagement | $30K | $50K |
| Primary tech stack | TensorFlow, PyTorch, Python | Python, TensorFlow, PyTorch |
| Industries served | fintech, e-commerce, healthcare, entertainment, media | financial services, healthcare, retail, media, government |
Miquido vs EPAM Systems: overview
Miquido
Miquido is a Google-certified software development company founded in 2011 and headquartered in Krakow, Poland. The company employs 150–300 professionals and has delivered 250+ digital products for clients including Warner, Dolby, Abbey Road Studios, Skyscanner, and TUI. Miquido's ML practice is distinguished by its integration with product design expertise — delivering machine learning inside well-crafted user experiences rather than as isolated algorithmic components.
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: Miquido vs EPAM Systems
| Capability | Miquido | EPAM Systems |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| ML consulting | ✓ | ✓ |
| Deep learning | ✗ | ✗ |
| NLP | ✓ | ✗ |
| Computer vision | ✓ | ✗ |
| MLOps | ✗ | ✓ |
| Predictive analytics | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| Data engineering | ✗ | ✓ |
| Staff augmentation | ✗ | ✓ |
Tech stack comparison: Miquido vs EPAM Systems
| Framework / platform | Miquido | EPAM Systems |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| Scikit-Learn | N/A | 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: Miquido vs EPAM Systems
| Criterion | Miquido | EPAM Systems |
|---|---|---|
| Minimum engagement | $30K | $50K |
| Engagement models | Fixed project, Dedicated team, T&M | Dedicated team, T&M, Fixed project, Staff augmentation |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Miquido vs EPAM Systems
| Dimension | Miquido | EPAM Systems |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | fintech, e-commerce, healthcare | financial services, healthcare, retail |
| Best use cases | ML feature integration into mobile and web consumer products (e.g., recommendation, personalization), Computer vision feature development for entertainment or retail apps | 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 |
Miquido vs EPAM Systems: pros and cons
| Miquido | |
|---|---|
| + | Google-certified partnership confirms cloud ML deployment capability on GCP independently |
| + | Named enterprise clients (Warner, Dolby, Skyscanner, TUI) verify delivery at brand scale |
| + | ML plus product design combination delivers end-user-facing AI features, not back-end-only models |
| + | 9/10 projects from referrals signals strong client satisfaction and delivery consistency |
| + | Krakow base with North American, European, and Middle Eastern client experience |
| - | Hourly rates ($70–$150) are higher than Eastern European average for similar team size |
| - | Product-first focus may mean less depth in complex research-adjacent ML or custom model architectures |
| - | Less visible in the US market compared to North American competitors of equivalent capability |
| 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 Miquido?
Miquido is the right choice for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise.
Google-certified AI/ML capability paired with strong product design — clients receive ML that works inside well-crafted user experiences, not bolted-on algorithms. Minimum engagement starts at $30K. Works best with clients in fintech, e-commerce, healthcare, entertainment, media.
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: Miquido vs EPAM Systems
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Miquido |
| You need a large dedicated team for an ongoing programme | Miquido |
| Your budget is at the lower end | Miquido |
| You need specialist depth in a specific vertical | Miquido |
| You need staff augmentation or team extension | EPAM Systems |
| You need consulting before committing to a build | Miquido |
Use case fit: Miquido vs EPAM Systems
| Use case | Miquido fit | EPAM Systems fit | Winner |
|---|---|---|---|
| ML feature integration into mobile and web consumer products (e.g., recommendation, personalization) | Strong | Strong | Both equally |
| Computer vision feature development for entertainment or retail apps | Strong | Limited | Miquido |
| 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: Miquido vs EPAM Systems
Miquido (4.0/5) is the stronger overall choice for most Machine Learning Development projects. Google-certified AI/ML capability paired with strong product design — clients receive ML that works inside well-crafted user experiences, not bolted-on algorithms. It is best for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise.
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
Miquido vs EPAM Systems FAQ
Is Miquido better than EPAM Systems?
Miquido (4.0/5) scores higher overall, but "better" depends on your use case. Miquido is better for product teams needing ML embedded inside polished digital products, with Google-certified cloud deployment and design expertise. 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 Miquido and EPAM Systems differ in pricing?
Miquido uses fixed project, dedicated team, t&m pricing with a minimum engagement of $30K. 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: Miquido or EPAM Systems?
Miquido 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 Miquido and EPAM Systems?
Miquido's primary differentiator is: google-certified ai/ml capability paired with strong product design — clients receive ml that works inside well-crafted user experiences, not bolted-on algorithms. 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 (150–300 vs 62,000+), minimum engagement ($30K vs $50K), and primary industries served (fintech, e-commerce vs financial services, healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.