ML6 vs WeAreBrain: full comparison for 2026
Last updated: July 2026
Quick verdict
ML6 (4.7/5) edges ahead of WeAreBrain (4.2/5) overall. ML6 is the better choice for enterprises needing production MLOps infrastructure and multi-cloud AI engineering at scale. WeAreBrain is the stronger option for companies wanting AI and machine learning delivered as part of a broader digital product build. The right choice depends on your project size, budget, and required tech stack.
ML6 vs WeAreBrain: head-to-head summary
| Criterion | ML6 | WeAreBrain |
|---|---|---|
| Founded | 2013 | 2015 |
| HQ | Ghent, Belgium | Amsterdam, Netherlands |
| Team size | 51–200 | 51–200 |
| Rating | 4.7 / 5 | 4.2 / 5 |
| Best for | Enterprises needing production MLOps infrastructure and multi-cloud AI engineering at scale | Companies wanting AI and machine learning delivered as part of a broader digital product build |
| Pricing model | Dedicated team, fixed project, retainer | Fixed project, dedicated team |
| Min. engagement | $40K | $25K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, AWS, Azure |
| Industries served | Enterprise, Financial Services, Retail, Manufacturing, Public Sector | SaaS, Fintech, Enterprise, Retail |
ML6 vs WeAreBrain: 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.
WeAreBrain
WeAreBrain is an Amsterdam, Netherlands-headquartered digital product and AI agency founded in 2015 by Mario Grunitz, Elvire Jaspers, and Ievgen Miasushkin. The roughly 60 to 70 person team specializes in digital transformation, AI and machine learning applications, and intelligent process automation. In 2017, WeAreBrain co-founded Tur.ai, an AI and hyperautomation platform with joint Amsterdam and Kyiv operations, reflecting the founders' Ukrainian engineering ties.
Services and capabilities: ML6 vs WeAreBrain
| Capability | ML6 | WeAreBrain |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✓ | ✗ |
| MLOps | ✓ | ✓ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: ML6 vs WeAreBrain
| Framework / platform | ML6 | WeAreBrain |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS | N/A | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | ✓ | N/A |
Pricing comparison: ML6 vs WeAreBrain
| Criterion | ML6 | WeAreBrain |
|---|---|---|
| Minimum engagement | $40K | $25K |
| Engagement models | Dedicated team, Fixed project, Retainer | Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: ML6 vs WeAreBrain
| Dimension | ML6 | WeAreBrain |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Enterprise, Financial Services, Retail | SaaS, Fintech, Enterprise |
| Best use cases | Building enterprise-scale MLOps pipelines, Deploying computer vision for manufacturing quality control | Building an AI-powered consumer-facing digital product, Intelligent process automation for back-office workflows |
| Typical project type | Dedicated team | Fixed project |
ML6 vs WeAreBrain: 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 |
| WeAreBrain | |
|---|---|
| + | A decade of operating history since founding in 2015 as an Amsterdam-based digital product agency |
| + | Co-founded a dedicated AI and hyperautomation platform, Tur.ai, showing deeper AI investment beyond client services |
| + | Combines product design with ML and AI engineering, useful for consumer-facing AI products |
| + | EU-headquartered in the Netherlands, simplifying GDPR compliance for European clients |
| - | AI and ML is one of several practice areas alongside broader digital product work |
| - | Some delivery ties to Kyiv, Ukraine via the Tur.ai venture carry the same continuity considerations as other Ukraine-linked firms |
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 WeAreBrain?
WeAreBrain is the right choice for companies wanting AI and machine learning delivered as part of a broader digital product build.
Digital product agency DNA combined with a dedicated AI, ML, and intelligent automation practice. Minimum engagement starts at $25K. Works best with clients in SaaS, Fintech, Enterprise, Retail.
Decision matrix: ML6 vs WeAreBrain
| 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 | WeAreBrain |
| 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 WeAreBrain
| Use case | ML6 fit | WeAreBrain fit | Winner |
|---|---|---|---|
| Building enterprise-scale MLOps pipelines | Strong | Strong | Both equally |
| Deploying computer vision for manufacturing quality control | Strong | Limited | ML6 |
| Building an AI-powered consumer-facing digital product | Strong | Strong | Both equally |
| Intelligent process automation for back-office workflows | Limited | Strong | WeAreBrain |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: ML6 vs WeAreBrain
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.
WeAreBrain (4.2/5) is the better choice when companies wanting AI and machine learning delivered as part of a broader digital product build. If your situation matches those criteria, WeAreBrain is a competitive option.
Related comparisons
ML6 vs WeAreBrain FAQ
Is ML6 better than WeAreBrain?
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. WeAreBrain is better for companies wanting AI and machine learning delivered as part of a broader digital product build.
How do ML6 and WeAreBrain differ in pricing?
ML6 uses dedicated team, fixed project, retainer pricing with a minimum engagement of $40K. WeAreBrain uses fixed project, dedicated team pricing with a minimum engagement of $25K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: ML6 or WeAreBrain?
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 WeAreBrain?
ML6's primary differentiator is: official openai services partner status combined with over a decade of pure-play ml engineering focus. WeAreBrain's primary differentiator is: digital product agency dna combined with a dedicated ai, ml, and intelligent automation practice. They also differ in team size (51–200 vs 51–200), minimum engagement ($40K vs $25K), and primary industries served (Enterprise, Financial Services vs SaaS, Fintech).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.