Best Machine Learning Development Companies in Europe

ML6 vs SDG Group: full comparison for 2026

Last updated: July 2026

Quick verdict

ML6 (4.7/5) edges ahead of SDG Group (3.7/5) overall. ML6 is the better choice for enterprises needing production MLOps infrastructure and multi-cloud AI engineering at scale. SDG Group is the stronger option for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme. The right choice depends on your project size, budget, and required tech stack.

ML6 vs SDG Group: head-to-head summary

Criterion ML6 SDG Group
Founded 2013 1994
HQ Ghent, Belgium Milan, Italy
Team size 51–200 1000+
Rating 4.7 / 5 3.7 / 5
Best for Enterprises needing production MLOps infrastructure and multi-cloud AI engineering at scale Large enterprises wanting ML-driven analytics embedded within a broader business performance management programme
Pricing model Dedicated team, fixed project, retainer Retainer, dedicated team, fixed project
Min. engagement $40K $50K
Primary tech stack Python, TensorFlow, PyTorch Python, Power BI, Tableau
Industries served Enterprise, Financial Services, Retail, Manufacturing, Public Sector Enterprise, Financial Services, Retail, Telecommunications

ML6 vs SDG Group: overview

ML6

ML6 is a Ghent, Belgium-headquartered AI engineering company founded in 2013 by Michael Lemmer and Nicolas Deruytter. With roughly 150 AI and ML specialists, ML6 is one of Europe's most established pure-play ML consultancies, known for MLOps, computer vision, and enterprise AI infrastructure work. The company was named an OpenAI Services Partner and is a Google Cloud partner, reflecting deep hands-on delivery experience across major model providers.

SDG Group

SDG Group, founded in 1994 and headquartered in Milan, Italy, is a global management consulting firm with roughly 2,000 employees and offices spanning Milan, Barcelona, London, and beyond. SDG Group specializes in business performance management and analytical applications, with machine learning and AI delivered as part of its broader business intelligence and enterprise analytics consulting practice.

Services and capabilities: ML6 vs SDG Group

Capability ML6 SDG Group
ML model development
Computer vision
NLP
Generative AI / LLM integration
MLOps
AI strategy consulting
Staff augmentation

Tech stack comparison: ML6 vs SDG Group

Framework / platform ML6 SDG Group
Python
TensorFlow N/A
PyTorch N/A
AWS N/A
Azure N/A
Kubernetes N/A

Pricing comparison: ML6 vs SDG Group

Criterion ML6 SDG Group
Minimum engagement $40K $50K
Engagement models Dedicated team, Fixed project, Retainer Retainer, Dedicated team, Fixed project
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: ML6 vs SDG Group

Dimension ML6 SDG Group
Best company size Startup to mid-market Startup to mid-market
Best industries Enterprise, Financial Services, Retail Enterprise, Financial Services, Retail
Best use cases Building enterprise-scale MLOps pipelines, Deploying computer vision for manufacturing quality control Enterprise business performance management with an ML component, Large-scale analytical applications for finance or retail clients
Typical project type Dedicated team Retainer

ML6 vs SDG Group: pros and cons

ML6
+ One of Europe's longest-running pure-play ML engineering firms, founded in 2013
+ Official OpenAI Services Partner and Google Cloud partner
+ Deep MLOps and production infrastructure expertise, not just model prototyping
+ 150-person specialist team with dedicated practice areas across computer vision, NLP, and MLOps
- Higher minimum engagement size than boutique competitors, less suited to small startups
- Primarily Benelux-based delivery, fewer nearshore options for very tight budgets
SDG Group
+ Three decades of operating history since founding in 1994, as a global management consulting firm
+ Enterprise-scale delivery capacity of roughly 2,000 staff across multiple European and international offices
+ Deep business performance management heritage grounds AI work in measurable business outcomes
+ Established relationships with large enterprise clients across multiple industries
- AI and ML is embedded within a much broader business intelligence and management consulting practice, not a dedicated specialization
- High minimum engagement size, inaccessible for startups or small businesses
- Management-consulting-led engagement model may add overhead versus lean engineering-only ML shops

Who should choose ML6?

ML6 is the right choice for enterprises needing production MLOps infrastructure and multi-cloud AI engineering at scale.

Official OpenAI Services Partner status combined with over a decade of pure-play ML engineering focus. Minimum engagement starts at $40K. Works best with clients in Enterprise, Financial Services, Retail, Manufacturing, Public Sector.

Who should choose SDG Group?

SDG Group is the right choice for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme.

Three decades of management consulting heritage applied to enterprise-scale analytics and AI programmes. Minimum engagement starts at $50K. Works best with clients in Enterprise, Financial Services, Retail, Telecommunications.

Decision matrix: ML6 vs SDG Group

Your situation Recommended choice
You need full-ownership delivery on a defined project scope ML6
You need a large dedicated team for an ongoing programme ML6
Your budget is at the lower end ML6
You need specialist depth in a specific vertical ML6
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build ML6

Use case fit: ML6 vs SDG Group

Use case ML6 fit SDG Group fit Winner
Building enterprise-scale MLOps pipelines Strong Limited ML6
Deploying computer vision for manufacturing quality control Strong Limited ML6
Enterprise business performance management with an ML component Strong Strong Both equally
Large-scale analytical applications for finance or retail clients Limited Strong SDG Group
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: ML6 vs SDG Group

ML6 (4.7/5) is the stronger overall choice for most Machine Learning Development projects. Official OpenAI Services Partner status combined with over a decade of pure-play ML engineering focus. It is best for enterprises needing production MLOps infrastructure and multi-cloud AI engineering at scale.

SDG Group (3.7/5) is the better choice when large enterprises wanting ML-driven analytics embedded within a broader business performance management programme. If your situation matches those criteria, SDG Group is a competitive option.

Related comparisons

ML6 vs SDG Group FAQ

Is ML6 better than SDG Group?

ML6 (4.7/5) scores higher overall, but "better" depends on your use case. ML6 is better for enterprises needing production MLOps infrastructure and multi-cloud AI engineering at scale. SDG Group is better for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme.

How do ML6 and SDG Group differ in pricing?

ML6 uses dedicated team, fixed project, retainer pricing with a minimum engagement of $40K. SDG Group uses retainer, dedicated team, fixed project 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: ML6 or SDG Group?

ML6 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 ML6 and SDG Group?

ML6's primary differentiator is: official openai services partner status combined with over a decade of pure-play ml engineering focus. SDG Group's primary differentiator is: three decades of management consulting heritage applied to enterprise-scale analytics and ai programmes. They also differ in team size (51–200 vs 1000+), minimum engagement ($40K vs $50K), and primary industries served (Enterprise, Financial Services vs Enterprise, Financial Services).

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