Miquido vs Keyrus: full comparison for 2026
Last updated: July 2026
Quick verdict
Miquido (4.2/5) edges ahead of Keyrus (3.8/5) overall. Miquido is the better choice for product companies and scale-ups needing ML features embedded within polished mobile or web products. Keyrus is the stronger option for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. The right choice depends on your project size, budget, and required tech stack.
Miquido vs Keyrus: head-to-head summary
| Criterion | Miquido | Keyrus |
|---|---|---|
| Founded | 2011 | 2000 |
| HQ | Kraków, Poland | Paris, France |
| Team size | 200+ | 3,500+ |
| Rating | 4.2 / 5 | 3.8 / 5 |
| Best for | Product companies and scale-ups needing ML features embedded within polished mobile or web products | International enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience |
| Pricing model | Fixed project, T&M | T&M, retainer |
| Min. engagement | $25K+ | $50K+ |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Tableau, Power BI |
| Industries served | saas, media, retail, healthcare, fintech | financial, retail, healthcare, manufacturing, media |
Miquido vs Keyrus: overview
Miquido
Miquido was founded in 2011 and is headquartered in Kraków, Poland, with 200+ engineers. The company specialises in AI and ML development integrated within mobile and web product engineering, serving clients including Skyscanner and Abbey Road Studios (per Miquido Clutch profile and official website). Miquido is known for combining UI/UX engineering with AI capabilities — particularly computer vision, recommendation systems, and NLP — for product-driven clients.
Keyrus
Keyrus is an international consulting group founded in 2000, headquartered in Paris, France, and operating in over 20 countries with 3,500+ professionals. The company positions itself at the intersection of business, data, and AI — helping clients move from experimental AI to industrial-grade ML systems in production. Services span data strategy, BI, analytics, AI testing, and ML deployment. (Employee count and global footprint per Keyrus official website.)
Services and capabilities: Miquido vs Keyrus
| Capability | Miquido | Keyrus |
|---|---|---|
| Custom ML build | ✓ | ✗ |
| ML consulting | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP / LLM | ✓ | ✗ |
| Predictive analytics | ✓ | ✓ |
| MLOps | ✗ | ✓ |
| Data engineering | ✗ | ✓ |
| Generative AI | ✗ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Fixed-price projects | ✓ | ✗ |
| Dedicated team model | ✗ | ✓ |
Tech stack comparison: Miquido vs Keyrus
| Framework / platform | Miquido | Keyrus |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
Pricing comparison: Miquido vs Keyrus
| Criterion | Miquido | Keyrus |
|---|---|---|
| Minimum engagement | $25K+ | $50K+ |
| Engagement models | Fixed project, T&M, Retainer | T&M, Retainer, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Miquido vs Keyrus
| Dimension | Miquido | Keyrus |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | saas, media, retail | financial, retail, healthcare |
| Best use cases | AI features within mobile travel app, Recommendation system for media platform | Industrial AI deployment at enterprise scale, Analytics and ML platform for financial services |
| Typical project type | Fixed project | T&M |
Miquido vs Keyrus: pros and cons
| Miquido | |
|---|---|
| + | Strong integration of ML with product and UI engineering — rare combination |
| + | Named clients include Skyscanner and Abbey Road Studios |
| + | Full product lifecycle capability: design to ML to mobile/web delivery |
| + | Kraków studio with transparent pricing and verifiable Clutch reviews |
| + | Computer vision and NLP experience in production applications |
| - | Less suitable for standalone ML research or data science consulting |
| - | Product engineering focus means less depth in MLOps or large-scale data infrastructure |
| Keyrus | |
|---|---|
| + | Global footprint: 20+ countries, 3,500+ professionals |
| + | Industrial-AI focus — moves clients from PoC to production scale |
| + | Strong analytics and BI alongside ML for full data stack coverage |
| + | AI testing and validation capability |
| - | Large-firm pricing not suited to startup or SMB budgets |
| - | AI is one offering within broader data consulting — not ML-first |
Who should choose Miquido?
Miquido is the right choice for product companies and scale-ups needing ML features embedded within polished mobile or web products.
AI-plus-product development — ML capabilities integrated with UX engineering, not delivered as a standalone model. Minimum engagement starts at $25K+. Works best with clients in saas, media, retail, healthcare, fintech.
Who should choose Keyrus?
Keyrus is the right choice for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience.
From experimental AI to industrial AI — consulting group specialising in productionising ML for large organisations. Minimum engagement starts at $50K+. Works best with clients in financial, retail, healthcare, manufacturing, media.
Decision matrix: Miquido vs Keyrus
| 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 | Keyrus |
| Your budget is at the lower end | Miquido |
| You need specialist depth in a specific vertical | Miquido |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Miquido |
Use case fit: Miquido vs Keyrus
| Use case | Miquido fit | Keyrus fit | Winner |
|---|---|---|---|
| AI features within mobile travel app | Strong | Strong | Both equally |
| Recommendation system for media platform | Strong | Limited | Miquido |
| Industrial AI deployment at enterprise scale | Limited | Strong | Keyrus |
| Analytics and ML platform for financial services | Limited | Strong | Keyrus |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Miquido vs Keyrus
Miquido (4.2/5) is the stronger overall choice for most Machine Learning projects. AI-plus-product development — ML capabilities integrated with UX engineering, not delivered as a standalone model. It is best for product companies and scale-ups needing ML features embedded within polished mobile or web products.
Keyrus (3.8/5) is the better choice when international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. If your situation matches those criteria, Keyrus is a competitive option.
Related comparisons
Miquido vs Keyrus FAQ
Is Miquido better than Keyrus?
Miquido (4.2/5) scores higher overall, but "better" depends on your use case. Miquido is better for product companies and scale-ups needing ML features embedded within polished mobile or web products. Keyrus is better for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience.
How do Miquido and Keyrus differ in pricing?
Miquido uses fixed project, t&m pricing with a minimum engagement of $25K+. Keyrus uses t&m, retainer 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 Keyrus?
Keyrus is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Miquido and Keyrus?
Miquido's primary differentiator is: ai-plus-product development — ml capabilities integrated with ux engineering, not delivered as a standalone model. Keyrus's primary differentiator is: from experimental ai to industrial ai — consulting group specialising in productionising ml for large organisations. They also differ in team size (200+ vs 3,500+), minimum engagement ($25K+ vs $50K+), and primary industries served (saas, media vs financial, retail).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.