Best Machine Learning Development Companies in Europe

STX Next vs Imaginary Cloud: full comparison for 2026

Last updated: July 2026

Quick verdict

STX Next (4.3/5) edges ahead of Imaginary Cloud (4.0/5) overall. STX Next is the better choice for companies needing ML development paired with deep, large-scale Python software engineering capacity. Imaginary Cloud is the stronger option for companies wanting ML capabilities delivered alongside strong product design and UX engineering. The right choice depends on your project size, budget, and required tech stack.

STX Next vs Imaginary Cloud: head-to-head summary

Criterion STX Next Imaginary Cloud
Founded 2005 2010
HQ Poznan, Poland Lisbon, Portugal
Team size 201–500 51–200
Rating 4.3 / 5 4.0 / 5
Best for Companies needing ML development paired with deep, large-scale Python software engineering capacity Companies wanting ML capabilities delivered alongside strong product design and UX engineering
Pricing model Dedicated team, staff augmentation, fixed project Fixed project, dedicated team
Min. engagement $25K $20K
Primary tech stack Python, Django, FastAPI Python, React, Node.js
Industries served SaaS, Fintech, Healthcare, E-commerce, Enterprise SaaS, Fintech, Healthcare, E-commerce

STX Next vs Imaginary Cloud: overview

STX Next

STX Next, founded in March 2005 in Poznan, Poland, grew from an 8-person startup into a nearly 500-person Python engineering firm with delivery centers across Poland and Mexico. Known primarily as one of Europe's largest dedicated Python engineering companies, STX Next has built out AI/ML and data engineering practices on top of its deep Python bench, making it a strong generalist option for ML projects that also require broader software engineering.

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.

Services and capabilities: STX Next vs Imaginary Cloud

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

Tech stack comparison: STX Next vs Imaginary Cloud

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

Pricing comparison: STX Next vs Imaginary Cloud

Criterion STX Next Imaginary Cloud
Minimum engagement $25K $20K
Engagement models Dedicated team, Staff augmentation, Fixed project Fixed project, Dedicated team
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: STX Next vs Imaginary Cloud

Dimension STX Next Imaginary Cloud
Best company size Startup to mid-market Startup to mid-market
Best industries SaaS, Fintech, Healthcare SaaS, Fintech, Healthcare
Best use cases ML feature development inside a larger Python software platform, Scaling an engineering team with dedicated Python and ML staff AI-enabled consumer product design and development, Custom software with embedded ML recommendation features
Typical project type Dedicated team Fixed project

STX Next vs Imaginary Cloud: pros and cons

STX Next
+ Two decades of operating history since founding in 2005 with proven scale of roughly 500 engineers
+ Deep Python engineering bench supports complex ML and software integration projects
+ Multiple delivery centers across Poland and Mexico for coverage flexibility
+ Established staff augmentation model for teams needing to scale quickly
- ML and AI is one practice among several rather than the firm's sole focus
- Larger organizational size may mean less founder-level attention than boutique specialists
- Best fit skews toward Python-centric stacks rather than polyglot ML environments
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

Who should choose STX Next?

STX Next is the right choice for companies needing ML development paired with deep, large-scale Python software engineering capacity.

One of Europe's largest dedicated Python engineering companies, with ML and data practices built on that scale. Minimum engagement starts at $25K. Works best with clients in SaaS, Fintech, Healthcare, E-commerce, Enterprise.

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.

Decision matrix: STX Next vs Imaginary Cloud

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

Use case fit: STX Next vs Imaginary Cloud

Use case STX Next fit Imaginary Cloud fit Winner
ML feature development inside a larger Python software platform Strong Strong Both equally
Scaling an engineering team with dedicated Python and ML staff Strong Limited STX Next
AI-enabled consumer product design and development Limited Strong Imaginary Cloud
Custom software with embedded ML recommendation features Limited Strong Imaginary Cloud
Fixed-price build Limited Limited Both equally
Staff augmentation Strong Limited STX Next

Verdict: STX Next vs Imaginary Cloud

STX Next (4.3/5) is the stronger overall choice for most Machine Learning Development projects. One of Europe's largest dedicated Python engineering companies, with ML and data practices built on that scale. It is best for companies needing ML development paired with deep, large-scale Python software engineering capacity.

Imaginary Cloud (4.0/5) is the better choice when companies wanting ML capabilities delivered alongside strong product design and UX engineering. If your situation matches those criteria, Imaginary Cloud is a competitive option.

Related comparisons

STX Next vs Imaginary Cloud FAQ

Is STX Next better than Imaginary Cloud?

STX Next (4.3/5) scores higher overall, but "better" depends on your use case. STX Next is better for companies needing ML development paired with deep, large-scale Python software engineering capacity. Imaginary Cloud is better for companies wanting ML capabilities delivered alongside strong product design and UX engineering.

How do STX Next and Imaginary Cloud differ in pricing?

STX Next uses dedicated team, staff augmentation, fixed project pricing with a minimum engagement of $25K. Imaginary Cloud uses fixed project, dedicated team 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: STX Next or Imaginary Cloud?

STX Next 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 STX Next and Imaginary Cloud?

STX Next's primary differentiator is: one of europe's largest dedicated python engineering companies, with ml and data practices built on that scale. Imaginary Cloud's primary differentiator is: design-led software development studio with ai positioned as a first-class capability, not an afterthought. They also differ in team size (201–500 vs 51–200), minimum engagement ($25K vs $20K), and primary industries served (SaaS, Fintech vs SaaS, Fintech).

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