Best Machine Learning Development Companies in Europe

Plain Concepts

Madrid-founded Microsoft Gold and AI Partner delivering AI, mixed reality, and cloud engineering since 2006.

Founded 2006 | Madrid, Spain | 201–500 employees | Last updated: July 2026
ml-developmentai-consultingmlopsdata-engineering

What is Plain Concepts?

Plain Concepts, founded in 2006 and headquartered in Madrid, Spain, is a 450-plus person technology consultancy with offices across the USA, UK, Spain, Germany, the Netherlands, and Romania. As a Microsoft Gold Partner, Microsoft AI Partner, and 2016 Microsoft Partner of the Year, Plain Concepts brings deep Azure-native AI and machine learning delivery experience alongside mixed reality and IoT engineering.

Plain Concepts was founded in 2006 and is headquartered in Madrid, Spain. The firm employs 201–500 people and works primarily with clients in Enterprise, Retail, Healthcare, Financial Services sectors. Its primary differentiator is: Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise.

Plain Concepts tech stack and services

PythonAzure MLAzure OpenAI Service.NETPower BIKubernetes
Service area Details
Azure-native ML model deployment for an enterprise client Available for Enterprise, Retail, Healthcare, Financial Services clients
Mixed reality plus AI product development Available for Enterprise, Retail, Healthcare, Financial Services clients
Microsoft-ecosystem AI modernization programmes Available for Enterprise, Retail, Healthcare, Financial Services clients
Enterprise IoT with embedded predictive analytics Available for Enterprise, Retail, Healthcare, Financial Services clients

Plain Concepts use cases

Short answer: Plain Concepts is best suited for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery.

Use case Industries Approach
Azure-native ML model deployment for an enterprise client Enterprise, Retail Python, Azure ML
Mixed reality plus AI product development Enterprise, Retail Python, Azure ML
Microsoft-ecosystem AI modernization programmes Enterprise, Retail Python, Azure ML
Enterprise IoT with embedded predictive analytics Enterprise, Retail Python, Azure ML

Plain Concepts pricing

Short answer: Plain Concepts uses a dedicated team, fixed project, retainer pricing approach. Minimum engagement starts at $35K.

Engagement model Typical range Best for
Dedicated team Variable; depends on team size Large programmes or team augmentation
Fixed project From $35K Well-defined scope
Retainer Monthly rate; not public Ongoing AI engineering
Plain Concepts does not publish a public rate card. Contact them directly via their website to get project-specific pricing.

Plain Concepts pros and cons

Advantages Things to consider
+Two decades of operating history since founding in 2006, with Microsoft Gold and AI Partner status -Azure-centric specialization may be less ideal for clients standardized on AWS or GCP
+Multi-country office footprint across Spain, the UK, Germany, the Netherlands, Romania, and the US for broad coverage -Broader technology consultancy scope, including mixed reality and IoT, means ML is one of several core practices
+Deep Azure-native ML and AI delivery credentials, useful for Microsoft-standardized enterprises -Larger enterprise-oriented engagement sizes, less accessible for very small startup budgets
+Recognized with Microsoft Partner of the Year award in 2016

Plain Concepts vs alternatives

How Plain Concepts compares to the other top Machine Learning Development companies.

Company Best for Key difference Rating Compare
Tensorway Startups and mid-market companies needing a dedicated, senior... Full-stack ML delivery team (data science, MLOps, QA) inherited from a 25-year-old parent company, at boutique-agency pricing 4.9 Full comparison
ML6 Enterprises needing production MLOps infrastructure and multi-cloud AI... Official OpenAI Services Partner status combined with over a decade of pure-play ML engineering focus 4.7 Full comparison
Alexander Thamm German and DACH-region manufacturers and industrial firms needing... Deep specialization in industrial and automotive ML use cases across the German Mittelstand 4.6 Full comparison
Kineo.ai Mid-market European businesses wanting a lean, senior AI... All-Germany team of AI consultants focused specifically on operational-efficiency ML use cases 4.6 Full comparison
DataRoot Labs Startups and SMBs needing a lean, senior custom... Founder-led, unfunded boutique with nearly a decade of focused custom ML delivery experience 4.5 Full comparison
Twistag Growth-stage and enterprise brands needing senior-engineer-only AI agent... Senior-only engineering team with a client roster including well-known global brands 4.5 Full comparison
Preste European companies needing custom computer vision or NLP... Dual Paris and Kyiv structure pairing French market presence with dedicated computer vision and NLP engineering delivery 4.4 Full comparison
STX Next Companies needing ML development paired with deep, large-scale... One of Europe's largest dedicated Python engineering companies, with ML and data practices built on that scale 4.3 Full comparison
Neoteric Mid-market companies wanting to move a generative AI... Two-decade-old Polish software house with a dedicated generative AI practice and a US-facing New York office 4.3 Full comparison
Tooploox Companies with genuinely hard ML and AI research-engineering... Research-grade ML engineering with peer-reviewed academic recognition at ECCV 2024, alongside client delivery 4.3 Full comparison
Opinov8 Enterprises and startups wanting AI embedded across a... AI treated as a foundational layer across the entire engineering lifecycle, not a bolt-on service 4.2 Full comparison
FELD M European enterprises wanting a long-established, multi-country data and... Over two decades of operating history since founding in 2002, with organic growth into a five-office pan-European practice 4.2 Full comparison
WeAreBrain Companies wanting AI and machine learning delivered as... Digital product agency DNA combined with a dedicated AI, ML, and intelligent automation practice 4.2 Full comparison
DATAFOREST Small and mid-market businesses needing data engineering plus... Combined data engineering (ETL) and ML analytics practice with a growing review base 4.1 Full comparison
Probayes Automotive, defense, and finance clients needing rigorous Bayesian... Over two decades of specialization in Bayesian AI and predictive analytics, predating the current ML and AI boom 4.1 Full comparison
Digica Regulated-industry clients such as automotive, defence, and medical... Combines ML model development with embedded systems and IoT engineering for regulated hardware-adjacent industries 4.1 Full comparison
Imaginary Cloud Companies wanting ML capabilities delivered alongside strong product... Design-led software development studio with AI positioned as a first-class capability, not an afterthought 4.0 Full comparison
N-iX Enterprises needing ML development bundled with large-scale custom... Over two decades of engineering scale, over 1,000 staff, with an EU-registered legal entity in Malta 4.0 Full comparison
Gemmo Companies wanting a structured, staged AI engagement, from... Structured three-phase engagement model of Pathfinder, Implementation, and Optimization, rather than an open-ended consulting retainer 4.0 Full comparison
Edvantis Enterprises wanting an EU-registered vendor with large-scale nearshore... EU legal registration in Poland combined with substantial delivery scale across Ukraine and Germany 3.9 Full comparison
CodeLeap Early-stage and growth-stage startups wanting fast, founder-friendly AI... Founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines 3.9 Full comparison
High-Tech Systems & Software Healthcare organizations needing AI and ML development bundled... Deep healthcare-sector software specialization in supply chain and telemedicine, with AI and ML layered on top 3.8 Full comparison
DEPT Large enterprise brands needing ML-driven marketing personalization at... Proprietary AI marketing platform, Ada, and global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list 4.0 Full comparison
Software Mind Enterprises needing ML development bundled with large-scale, multi-region... Over 25 years of operating history and enterprise-scale delivery capacity across three continents 3.8 Full comparison
Innowise Enterprises needing large-scale, low-cost nearshore staff augmentation with... Very large delivery scale and broad geographic reach, positioned for volume staff augmentation over specialist ML depth 3.8 Full comparison
BJSS UK public sector and regulated-industry clients needing enterprise-grade... Over three decades of operating history and deep specialization in regulated, complex enterprise environments 3.8 Full comparison
Siili Solutions Nordic and European enterprises wanting a publicly listed,... Publicly traded on Nasdaq Helsinki, offering financial transparency uncommon among privately held ML firms 3.7 Full comparison
SDG Group Large enterprises wanting ML-driven analytics embedded within a... Three decades of management consulting heritage applied to enterprise-scale analytics and AI programmes 3.7 Full comparison
Transparity UK enterprises fully standardized on Microsoft Azure wanting... Proprietary AI Factory framework built specifically around Microsoft Azure and Copilot technologies 3.7 Full comparison

Plain Concepts FAQ

What is Plain Concepts?

Plain Concepts, founded in 2006 and headquartered in Madrid, Spain, is a 450-plus person technology consultancy with offices across the USA, UK, Spain, Germany, the Netherlands, and Romania. As a Microsoft Gold Partner, Microsoft AI Partner, and 2016 Microsoft Partner of the Year, Plain Concepts brings deep Azure-native AI and machine learning delivery experience alongside mixed reality and IoT engineering.

How much does Plain Concepts charge?

Plain Concepts uses dedicated team, fixed project, retainer pricing. Minimum engagement starts at $35K. A discovery call is required to get project-specific quotes.

What tech stack does Plain Concepts use?

Plain Concepts works with Python, Azure ML, Azure OpenAI Service, .NET, Power BI, Kubernetes. Primary industries served include Enterprise, Retail, Healthcare, Financial Services.

Is Plain Concepts right for enterprise?

Enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. 201–500 team size. Key consideration: Azure-centric specialization may be less ideal for clients standardized on AWS or GCP.

What are the best Plain Concepts alternatives?

The best alternatives to Plain Concepts depend on your use case. Top options are:

  • Tensorway: full-stack ml delivery team (data science, mlops, qa) inherited from a 25-year-old parent company, at boutique-agency pricing
  • ML6: official openai services partner status combined with over a decade of pure-play ml engineering focus
  • Alexander Thamm: deep specialization in industrial and automotive ml use cases across the german mittelstand
See full alternatives list

Compare Plain Concepts with other Machine Learning Development companies

Last reviewed: July 2026. Verify all details directly with Plain Concepts before making a decision.