EPAM Systems vs Miquido: full comparison for 2026
Quick verdict
EPAM Systems (4.1/5) edges ahead of Miquido (3.9/5) overall. EPAM Systems is the better choice for enterprises with multi-year engineering budgets. Miquido is the stronger option for consumer apps adding AI features. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs Miquido: head-to-head summary
| Criterion | EPAM Systems | Miquido |
|---|---|---|
| Founded | 1993 | 2011 |
| HQ | Newtown, PA, USA | Kraków, Poland |
| Team size | 61,000+ | 180+ |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | Engineering capacity across Europe, India, and the Americas for long AI programs | Product design and mobile skills around the AI work |
| Pricing model | Time & materials and dedicated teams; rates on request | Fixed-scope projects and time & materials; $50–$99/hr (GoodFirms band) |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Azure OpenAI, AWS Bedrock, Databricks | n8n, Azure OpenAI, Google Cloud |
| Industries served | Financial services, Healthcare, Retail & e-commerce, Media, Energy | Financial services, Healthcare, Retail & e-commerce, Media |
EPAM Systems vs Miquido: overview
EPAM Systems
EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with over 61,200 employees at the end of 2025. Acquisitions shaped the recent mix: NEORIS (2024) for Latin America and Iberia, and First Derivative (completed December 2024) for financial-services data. Management targets more than $600 million of AI-native revenue in 2026, after reporting over $105 million in Q4 2025. Its AI/Run tooling and Agentic QA product support large engineering programs more than single-workflow pilots.
Miquido
Miquido is a Kraków software and product studio founded in 2011, with roughly 190–300 staff depending on the source. It started in mobile and product design and now offers generative AI, machine learning, voice assistants, and chatbots, plus an internal AI and automation team building workflows on n8n. Its strength is AI features that need a polished user interface around them. GoodFirms lists a $50–$99 hourly band.
Services and capabilities: EPAM Systems vs Miquido
| Capability | EPAM Systems | Miquido |
|---|---|---|
| CRM / ERP integration | ✓ | ✗ |
| LLM API gateway & cost control | ✓ | ✓ |
| Document processing | ✗ | ✗ |
| Conversational AI | ✗ | ✓ |
| Agentic workflows | ✓ | ✗ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✓ | ✗ |
Tech stack comparison: EPAM Systems vs Miquido
| Framework / platform | EPAM Systems | Miquido |
|---|---|---|
| Salesforce | N/A | N/A |
| SAP | ✓ | N/A |
| Microsoft Dynamics 365 | N/A | N/A |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | N/A |
| Databricks | ✓ | N/A |
| BigQuery | N/A | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | ✓ | N/A |
| Zendesk | N/A | N/A |
Pricing comparison: EPAM Systems vs Miquido
| Criterion | EPAM Systems | Miquido |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Time & materials, Dedicated team, Managed services | Fixed-scope project, Time & materials |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs Miquido
| Dimension | EPAM Systems | Miquido |
|---|---|---|
| Best company size | Enterprise | Startup to mid-market |
| Best industries | Financial services, Healthcare, Retail & e-commerce | Financial services, Healthcare, Retail & e-commerce |
| Best use cases | Large data-platform programs that end in AI features, Agent development across several business units | Voice and chat assistants in banking apps, Workflow automations built on n8n |
| Typical project type | Time & materials | Fixed-scope project |
EPAM Systems vs Miquido: pros and cons
| EPAM Systems | |
|---|---|
| + | Engineering depth to staff many workstreams at once. |
| + | Public reporting on AI-native revenue gives a measurable view of the practice. |
| + | First Derivative added capital-markets data skills. |
| + | Agentic QA product addresses testing of AI-generated code. |
| - | Acquisition-driven growth (NEORIS, First Derivative) means teams are still being integrated |
| - | Not built for a small fixed-price pilot |
| - | Management flagged slower organic growth in 2026 guidance |
| Miquido | |
|---|---|
| + | Design and mobile teams make AI features usable for consumers. |
| + | n8n automation work suits lightweight process automation. |
| + | Mid-band European rates. |
| - | Enterprise system integration (ERP, data warehouses) isn't its strength |
| - | No Clutch pricing data found |
| - | Headcount figures vary from about 190 to 500 |
Who should choose EPAM Systems?
A typical fit: large data-platform programs that end in AI features.
Engineering capacity across Europe, India, and the Americas for long AI programs. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media, Energy.
Who should choose Miquido?
A typical fit: voice and chat assistants in banking apps.
Product design and mobile skills around the AI work. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media.
Decision matrix: EPAM Systems vs Miquido
| Your situation | Recommended choice |
|---|---|
| You want a priced pilot before committing to a rollout | Neither advertises one; ask for a scoped pilot quote |
| You need someone to run and monitor the system after launch | EPAM Systems |
| Your budget is at the lower end | Compare: EPAM Systems (Not disclosed) vs Miquido (Not disclosed) |
| The AI has to read and write in your CRM or ERP | EPAM Systems |
| You need multi-step agents acting across systems | EPAM Systems |
| You need a large team for a multi-year program | EPAM Systems |
Use case fit: EPAM Systems vs Miquido
| Use case | EPAM Systems fit | Miquido fit | Winner |
|---|---|---|---|
| Large data-platform programs that end in AI features | Strong | Limited | EPAM Systems |
| Agent development across several business units | Strong | Limited | EPAM Systems |
| Voice and chat assistants in banking apps | Limited | Strong | Miquido |
| Workflow automations built on n8n | Limited | Strong | Miquido |
Verdict: EPAM Systems vs Miquido
EPAM Systems (4.1/5) is the stronger overall choice for most AI Integration Services projects. Engineering capacity across Europe, India, and the Americas for long AI programs.
Miquido (3.9/5) is worth a look if you need workflow automations built on n8n. If your situation matches that, Miquido is a competitive option.
Related comparisons
EPAM Systems vs Miquido FAQ
Is EPAM Systems better than Miquido?
EPAM Systems (4.1/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: engineering depth to staff many workstreams at once. Miquido's strongest advantage: design and mobile teams make AI features usable for consumers.
How do EPAM Systems and Miquido differ in pricing?
EPAM Systems's pricing: time & materials and dedicated teams; rates on request. Miquido's pricing: fixed-scope projects and time & materials; $50–$99/hr (GoodFirms band). Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
Which is better for enterprise: EPAM Systems or Miquido?
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 provider before shortlisting.
What are the main differences between EPAM Systems and Miquido?
EPAM Systems's primary differentiator is: engineering capacity across Europe, India, and the Americas for long AI programs. Miquido's primary differentiator is: product design and mobile skills around the AI work. They also differ in team size (61,000+ vs 180+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Financial services, Healthcare).
Verify all details directly with each provider before making a decision.