Best Machine Learning Development Companies in Europe

Plain Concepts vs CodeLeap: full comparison for 2026

Last updated: July 2026

Quick verdict

Plain Concepts (3.9/5) edges ahead of CodeLeap (3.9/5) overall. Plain Concepts is the better choice for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. CodeLeap is the stronger option for early-stage and growth-stage startups wanting fast, founder-friendly AI feature development. The right choice depends on your project size, budget, and required tech stack.

Plain Concepts vs CodeLeap: head-to-head summary

Criterion Plain Concepts CodeLeap
Founded 2006 2019
HQ Madrid, Spain London, UK
Team size 201–500 11–50
Rating 3.9 / 5 3.9 / 5
Best for Enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery Early-stage and growth-stage startups wanting fast, founder-friendly AI feature development
Pricing model Dedicated team, fixed project, retainer Fixed project, dedicated team
Min. engagement $35K $15K
Primary tech stack Python, Azure ML, Azure OpenAI Service Python, React, Node.js
Industries served Enterprise, Retail, Healthcare, Financial Services SaaS, E-commerce, Fintech

Plain Concepts vs CodeLeap: overview

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.

CodeLeap

CodeLeap, registered as Codeleap Ltd in England, was founded in 2019 and is headquartered in London, UK. The agency works closely with startups and growth-stage companies to build digital products with AI features, positioning itself around speed and a founder-friendly delivery model rather than large-scale enterprise engagement.

Services and capabilities: Plain Concepts vs CodeLeap

Capability Plain Concepts CodeLeap
ML model development
Computer vision
NLP
Generative AI / LLM integration
MLOps
AI strategy consulting
Staff augmentation

Tech stack comparison: Plain Concepts vs CodeLeap

Framework / platform Plain Concepts CodeLeap
Python
TensorFlow N/A N/A
PyTorch N/A N/A
AWS N/A
Azure N/A
Kubernetes N/A

Pricing comparison: Plain Concepts vs CodeLeap

Criterion Plain Concepts CodeLeap
Minimum engagement $35K $15K
Engagement models Dedicated team, Fixed project, Retainer Fixed project, Dedicated team
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: Plain Concepts vs CodeLeap

Dimension Plain Concepts CodeLeap
Best company size Startup to mid-market Startup to mid-market
Best industries Enterprise, Retail, Healthcare SaaS, E-commerce, Fintech
Best use cases Azure-native ML model deployment for an enterprise client, Mixed reality plus AI product development Adding an AI feature to an early-stage startup product, Fast MVP development with an embedded ML component
Typical project type Dedicated team Fixed project

Plain Concepts vs CodeLeap: pros and cons

Plain Concepts
+ Two decades of operating history since founding in 2006, with Microsoft Gold and AI Partner status
+ Multi-country office footprint across Spain, the UK, Germany, the Netherlands, Romania, and the US for broad coverage
+ Deep Azure-native ML and AI delivery credentials, useful for Microsoft-standardized enterprises
+ Recognized with Microsoft Partner of the Year award in 2016
- Azure-centric specialization may be less ideal for clients standardized on AWS or GCP
- Broader technology consultancy scope, including mixed reality and IoT, means ML is one of several core practices
- Larger enterprise-oriented engagement sizes, less accessible for very small startup budgets
CodeLeap
+ Legally registered in England with a London-based, client-facing team
+ Founder-friendly delivery model designed specifically around startup speed and iteration
+ Lower minimum engagement size than most enterprise-oriented firms on this list
+ Focused specifically on AI-featured digital product builds rather than broad enterprise IT
- Founded in 2019, one of the newer and smaller firms on this list with a shorter track record
- Small team size of 11 to 50 limits capacity for large, multi-workstream programmes
- Less suited to heavily regulated enterprise ML programmes than larger specialist firms

Who should choose Plain Concepts?

Plain Concepts is the right choice for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery.

Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise. Minimum engagement starts at $35K. Works best with clients in Enterprise, Retail, Healthcare, Financial Services.

Who should choose CodeLeap?

CodeLeap is the right choice for early-stage and growth-stage startups wanting fast, founder-friendly AI feature development.

Founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines. Minimum engagement starts at $15K. Works best with clients in SaaS, E-commerce, Fintech.

Decision matrix: Plain Concepts vs CodeLeap

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Plain Concepts
You need a large dedicated team for an ongoing programme Plain Concepts
Your budget is at the lower end CodeLeap
You need specialist depth in a specific vertical Plain Concepts
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build Plain Concepts

Use case fit: Plain Concepts vs CodeLeap

Use case Plain Concepts fit CodeLeap fit Winner
Azure-native ML model deployment for an enterprise client Strong Limited Plain Concepts
Mixed reality plus AI product development Strong Limited Plain Concepts
Adding an AI feature to an early-stage startup product Limited Strong CodeLeap
Fast MVP development with an embedded ML component Limited Strong CodeLeap
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Plain Concepts vs CodeLeap

Plain Concepts (3.9/5) is the stronger overall choice for most Machine Learning Development projects. Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise. It is best for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery.

CodeLeap (3.9/5) is the better choice when early-stage and growth-stage startups wanting fast, founder-friendly AI feature development. If your situation matches those criteria, CodeLeap is a competitive option.

Related comparisons

Plain Concepts vs CodeLeap FAQ

Is Plain Concepts better than CodeLeap?

Plain Concepts (3.9/5) scores higher overall, but "better" depends on your use case. Plain Concepts is better for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. CodeLeap is better for early-stage and growth-stage startups wanting fast, founder-friendly AI feature development.

How do Plain Concepts and CodeLeap differ in pricing?

Plain Concepts uses dedicated team, fixed project, retainer pricing with a minimum engagement of $35K. CodeLeap uses fixed project, dedicated team pricing with a minimum engagement of $15K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Plain Concepts or CodeLeap?

Plain Concepts 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 Plain Concepts and CodeLeap?

Plain Concepts's primary differentiator is: deep azure-native ai and ml delivery credentials as a microsoft gold and ai partner, plus mixed reality expertise. CodeLeap's primary differentiator is: founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines. They also differ in team size (201–500 vs 11–50), minimum engagement ($35K vs $15K), and primary industries served (Enterprise, Retail vs SaaS, E-commerce).

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