Best Machine Learning Development Companies in Europe

Imaginary Cloud vs Innowise: full comparison for 2026

Last updated: July 2026

Quick verdict

Imaginary Cloud (4.0/5) edges ahead of Innowise (3.8/5) overall. Imaginary Cloud is the better choice for companies wanting ML capabilities delivered alongside strong product design and UX engineering. Innowise is the stronger option for enterprises needing large-scale, low-cost nearshore staff augmentation with an ML and AI component. The right choice depends on your project size, budget, and required tech stack.

Imaginary Cloud vs Innowise: head-to-head summary

Criterion Imaginary Cloud Innowise
Founded 2010 2007
HQ Lisbon, Portugal Warsaw, Poland
Team size 51–200 1000+
Rating 4.0 / 5 3.8 / 5
Best for Companies wanting ML capabilities delivered alongside strong product design and UX engineering Enterprises needing large-scale, low-cost nearshore staff augmentation with an ML and AI component
Pricing model Fixed project, dedicated team Staff augmentation, dedicated team, fixed project
Min. engagement $20K $20K
Primary tech stack Python, React, Node.js Python, Java, .NET
Industries served SaaS, Fintech, Healthcare, E-commerce Fintech, Healthcare, E-commerce, Enterprise

Imaginary Cloud vs Innowise: overview

Imaginary Cloud

Imaginary Cloud, founded in 2010 and headquartered in Lisbon, Portugal, is an AI-first software development company with roughly 77 employees. The firm combines design, engineering, and AI to deliver custom software and machine learning-enabled products, positioning itself around what it calls seamless digital acceleration, per company website.

Innowise

Innowise, also known as Innowise Group, founded in 2007 and headquartered in Warsaw, Poland, is a large IT outsourcing company with reported staff counts ranging from roughly 700 to over 3,000 depending on source and time period. Innowise offers AI and machine learning development as part of a broad custom software development, staff augmentation, and IT consulting portfolio spanning five continents.

Services and capabilities: Imaginary Cloud vs Innowise

Capability Imaginary Cloud Innowise
ML model development
Computer vision
NLP
Generative AI / LLM integration
MLOps
AI strategy consulting
Staff augmentation

Tech stack comparison: Imaginary Cloud vs Innowise

Framework / platform Imaginary Cloud Innowise
Python
TensorFlow
PyTorch N/A N/A
AWS
Azure N/A
Kubernetes N/A N/A

Pricing comparison: Imaginary Cloud vs Innowise

Criterion Imaginary Cloud Innowise
Minimum engagement $20K $20K
Engagement models Fixed project, Dedicated team Staff augmentation, Dedicated team, Fixed project
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: Imaginary Cloud vs Innowise

Dimension Imaginary Cloud Innowise
Best company size Startup to mid-market Startup to mid-market
Best industries SaaS, Fintech, Healthcare Fintech, Healthcare, E-commerce
Best use cases AI-enabled consumer product design and development, Custom software with embedded ML recommendation features Large-scale staff augmentation for an ML engineering team, Cost-sensitive nearshore development with an AI component
Typical project type Fixed project Staff augmentation

Imaginary Cloud vs Innowise: pros and cons

Imaginary Cloud
+ 15 years of operating history since founding in 2010 as a Lisbon-based software studio
+ Strong design and UX engineering complements ML and AI delivery for consumer-facing products
+ EU-headquartered in Portugal, useful for European data-residency requirements
+ Positions AI as a first-class design consideration, not a bolted-on backend feature
- Broader software and design studio heritage means ML depth is narrower than pure-play ML specialists
- Smaller team of around 77 relative to larger regional generalists on this list
Innowise
+ Nearly two decades of operating history since founding in 2007, with very large delivery scale
+ Broad staff augmentation offering useful for enterprises needing to scale ML teams quickly and cheaply
+ Presence across five continents provides flexible time-zone coverage
+ Lower minimum engagement size than several other large generalist firms on this list
- Reported employee counts vary substantially across sources, from roughly 700 to over 3,000, reflecting limited public transparency
- AI and ML is one service line within a very broad generalist IT outsourcing portfolio, not a specialist focus
- Volume-outsourcing model may deliver less senior-level attention than boutique ML specialists

Who should choose Imaginary Cloud?

Imaginary Cloud is the right choice for companies wanting ML capabilities delivered alongside strong product design and UX engineering.

Design-led software development studio with AI positioned as a first-class capability, not an afterthought. Minimum engagement starts at $20K. Works best with clients in SaaS, Fintech, Healthcare, E-commerce.

Who should choose Innowise?

Innowise is the right choice for enterprises needing large-scale, low-cost nearshore staff augmentation with an ML and AI component.

Very large delivery scale and broad geographic reach, positioned for volume staff augmentation over specialist ML depth. Minimum engagement starts at $20K. Works best with clients in Fintech, Healthcare, E-commerce, Enterprise.

Decision matrix: Imaginary Cloud vs Innowise

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Imaginary Cloud
You need a large dedicated team for an ongoing programme Imaginary Cloud
Your budget is at the lower end Imaginary Cloud
You need specialist depth in a specific vertical Imaginary Cloud
You need staff augmentation or team extension Innowise
You need consulting before committing to a build Imaginary Cloud

Use case fit: Imaginary Cloud vs Innowise

Use case Imaginary Cloud fit Innowise fit Winner
AI-enabled consumer product design and development Strong Limited Imaginary Cloud
Custom software with embedded ML recommendation features Strong Limited Imaginary Cloud
Large-scale staff augmentation for an ML engineering team Limited Strong Innowise
Cost-sensitive nearshore development with an AI component Limited Strong Innowise
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Strong Innowise

Verdict: Imaginary Cloud vs Innowise

Imaginary Cloud (4.0/5) is the stronger overall choice for most Machine Learning Development projects. Design-led software development studio with AI positioned as a first-class capability, not an afterthought. It is best for companies wanting ML capabilities delivered alongside strong product design and UX engineering.

Innowise (3.8/5) is the better choice when enterprises needing large-scale, low-cost nearshore staff augmentation with an ML and AI component. If your situation matches those criteria, Innowise is a competitive option.

Related comparisons

Imaginary Cloud vs Innowise FAQ

Is Imaginary Cloud better than Innowise?

Imaginary Cloud (4.0/5) scores higher overall, but "better" depends on your use case. Imaginary Cloud is better for companies wanting ML capabilities delivered alongside strong product design and UX engineering. Innowise is better for enterprises needing large-scale, low-cost nearshore staff augmentation with an ML and AI component.

How do Imaginary Cloud and Innowise differ in pricing?

Imaginary Cloud uses fixed project, dedicated team pricing with a minimum engagement of $20K. Innowise uses staff augmentation, dedicated team, fixed project pricing with a minimum engagement of $20K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Imaginary Cloud or Innowise?

Imaginary Cloud 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 Imaginary Cloud and Innowise?

Imaginary Cloud's primary differentiator is: design-led software development studio with ai positioned as a first-class capability, not an afterthought. Innowise's primary differentiator is: very large delivery scale and broad geographic reach, positioned for volume staff augmentation over specialist ml depth. They also differ in team size (51–200 vs 1000+), minimum engagement ($20K vs $20K), and primary industries served (SaaS, Fintech vs Fintech, Healthcare).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.