Addepto vs Miquido: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.4/5) edges ahead of Miquido (4.1/5) overall. Addepto is the better choice for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline.. Miquido is the stronger option for companies wanting AI and ML features — RAG, computer vision, on-device AI — integrated into a broader mobile or web product build.. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Miquido: head-to-head summary
| Criterion | Addepto | Miquido |
|---|---|---|
| Founded | 2017 | 2011 |
| HQ | Warsaw, Poland | Kraków, Poland |
| Team size | 50–249 | Not disclosed |
| Rating | 4.4 / 5 | 4.1 / 5 |
| Best for | Mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline. | Companies wanting AI and ML features — RAG, computer vision, on-device AI — integrated into a broader mobile or web product build. |
| Pricing model | Fixed project, Time & Materials | Fixed project, dedicated team |
| Min. engagement | $10,000+ | Not published |
| Primary tech stack | Python, MLOps pipelines, AWS | Python, On-device AI frameworks, Computer vision libraries |
| Industries served | Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics | Fintech, Healthcare, Retail/E-commerce, Energy & Utilities |
Addepto vs Miquido: overview
Addepto
Addepto is a Warsaw, Poland AI consultancy founded in 2017 that explicitly positions its value around production-grade delivery — moving clients from proof-of-concept to production — rather than research exploration. It covers AI consulting, generative AI development, data engineering, MLOps, document processing, and computer vision, serving aviation, manufacturing, automotive, finance, retail, healthcare, and logistics clients. Addepto is a GoodFirms top-rated firm for Big Data and Business Intelligence services, with a 50–249 employee band per Clutch.
Miquido
Miquido is a Kraków, Poland product-development company founded in 2011, offering on-device AI development, AI integration, computer vision, NLP, RAG development, and AI guardrails alongside its core mobile and web engineering practice. Notable clients include Warner Music, Universal, and Abbey Road Studios (per company website), and the company reports 90% of projects sourced from client referrals. Team size is not publicly disclosed.
Services and capabilities: Addepto vs Miquido
| Capability | Addepto | Miquido |
|---|---|---|
| ML Development | ✓ | ✓ |
| AI Consulting | ✓ | ✗ |
| Computer Vision | ✗ | ✓ |
| NLP | ✗ | ✓ |
| Generative AI | ✗ | ✓ |
| MLOps | ✓ | ✗ |
| Data Engineering | ✓ | ✗ |
| Staff Augmentation | ✗ | ✗ |
Tech stack comparison: Addepto vs Miquido
| Framework / platform | Addepto | Miquido |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | N/A |
| Microsoft Azure | N/A | N/A |
| Google Cloud | ✓ | N/A |
| Kubernetes | N/A | N/A |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: Addepto vs Miquido
| Criterion | Addepto | Miquido |
|---|---|---|
| Minimum engagement | $10,000+ | Not published |
| Engagement models | Fixed project, Time & Materials, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Enterprise / mid-market |
Target audience comparison: Addepto vs Miquido
| Dimension | Addepto | Miquido |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Aviation, Manufacturing, Automotive | Fintech, Healthcare, Retail/E-commerce |
| Best use cases | Computer vision for document processing, MLOps pipeline hardening for existing proof-of-concepts | On-device AI features for mobile apps, RAG-based AI product development |
| Typical project type | Fixed project | Fixed project |
Addepto vs Miquido: pros and cons
| Addepto | |
|---|---|
| + | Broad industry coverage from aviation to legal shows delivery flexibility beyond a single vertical |
| + | Explicit MLOps and production focus addresses the common 'stuck in proof-of-concept' failure mode |
| + | $10K entry point is accessible for a mid-market pilot engagement |
| + | GoodFirms top-rated recognition for Big Data and Business Intelligence services |
| - | Broad industry spread can mean less depth in any single regulated vertical than a specialist boutique |
| - | Exact team size within the 50–249 Clutch band is not broken out by function |
| - | Public case studies are largely testimonial-based rather than published with hard metrics |
| Miquido | |
|---|---|
| + | Notable enterprise and media clients including Warner Music, Universal, and Abbey Road Studios (per company website) |
| + | On-device AI and AI guardrails are a more specialized offering than most generalist dev shops provide |
| + | 90% of projects reportedly sourced from client referrals, suggesting strong repeat business (per company website) |
| + | Founded 2011 — over a decade of Kraków-based product engineering experience |
| - | Team size is not publicly disclosed |
| - | AI/ML is an extension of a broader mobile and web product engineering practice rather than the company's original core focus |
| - | Entertainment and music-industry client concentration may not translate to buyers in other regulated industries |
Who should choose Addepto?
Addepto is the right choice for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline..
Explicit 'proof-of-concept to production' positioning addresses the common failure mode where enterprise ML pilots never reach deployment.. Minimum engagement starts at $10,000+. Works best with clients in Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics.
Who should choose Miquido?
Miquido is the right choice for companies wanting AI and ML features — RAG, computer vision, on-device AI — integrated into a broader mobile or web product build..
Offers on-device AI development and AI guardrails alongside core ML, computer vision, and NLP work — a more product-engineering-centric AI offering than pure consulting-first competitors.. Minimum engagement starts at Not published. Works best with clients in Fintech, Healthcare, Retail/E-commerce, Energy & Utilities.
Decision matrix: Addepto vs Miquido
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Addepto |
| You need a large dedicated team for an ongoing programme | Addepto |
| Your budget is at the lower end | Compare: Addepto ($10,000+) vs Miquido (Not published) |
| You need specialist depth in a specific vertical | Addepto |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Addepto |
Use case fit: Addepto vs Miquido
| Use case | Addepto fit | Miquido fit | Winner |
|---|---|---|---|
| Computer vision for document processing | Strong | Strong | Both equally |
| MLOps pipeline hardening for existing proof-of-concepts | Strong | Limited | Addepto |
| On-device AI features for mobile apps | Limited | Strong | Miquido |
| RAG-based AI product development | Limited | Strong | Miquido |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Addepto vs Miquido
Addepto (4.4/5) is the stronger overall choice for most Machine Learning Development projects. Explicit 'proof-of-concept to production' positioning addresses the common failure mode where enterprise ML pilots never reach deployment.. It is best for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline..
Miquido (4.1/5) is the better choice when companies wanting AI and ML features — RAG, computer vision, on-device AI — integrated into a broader mobile or web product build.. If your situation matches those criteria, Miquido is a competitive option.
Related comparisons
Addepto vs Miquido FAQ
Is Addepto better than Miquido?
Addepto (4.4/5) scores higher overall, but "better" depends on your use case. Addepto is better for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline.. Miquido is better for companies wanting AI and ML features — RAG, computer vision, on-device AI — integrated into a broader mobile or web product build..
How do Addepto and Miquido differ in pricing?
Addepto uses fixed project, time & materials pricing with a minimum engagement of $10,000+. Miquido uses fixed project, dedicated team 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: Addepto or Miquido?
Addepto 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 Addepto and Miquido?
Addepto's primary differentiator is: explicit 'proof-of-concept to production' positioning addresses the common failure mode where enterprise ml pilots never reach deployment.. Miquido's primary differentiator is: offers on-device ai development and ai guardrails alongside core ml, computer vision, and nlp work — a more product-engineering-centric ai offering than pure consulting-first competitors.. They also differ in team size (50–249 vs Not disclosed), minimum engagement ($10,000+ vs Not published), and primary industries served (Aviation, Manufacturing vs Fintech, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.