WeAreBrain vs Reaktor: full comparison for 2026
Last updated: July 2026
Quick verdict
WeAreBrain (4.3/5) edges ahead of Reaktor (3.8/5) overall. WeAreBrain is the better choice for startups and scale-ups wanting AI-native product development combined with broader software modernization, not just an isolated ML model.. Reaktor is the stronger option for enterprises wanting AI capability embedded within a broader human-centred digital product and design consultancy, rather than a standalone ML vendor.. The right choice depends on your project size, budget, and required tech stack.
WeAreBrain vs Reaktor: head-to-head summary
| Criterion | WeAreBrain | Reaktor |
|---|---|---|
| Founded | 2015 | 2000 |
| HQ | Netherlands (internationally distributed team) | Helsinki, Finland |
| Team size | 60+ | 700 |
| Rating | 4.3 / 5 | 3.8 / 5 |
| Best for | Startups and scale-ups wanting AI-native product development combined with broader software modernization, not just an isolated ML model. | Enterprises wanting AI capability embedded within a broader human-centred digital product and design consultancy, rather than a standalone ML vendor. |
| Pricing model | Dedicated team, fixed project | Dedicated team, project-based consulting |
| Min. engagement | Not published | Not published (large enterprise engagements) |
| Primary tech stack | Python, AI product tooling, Shopify/SAP Commerce Cloud integrations | Python, AI/data-driven product tooling, Cloud platforms |
| Industries served | Transport & Logistics, Healthcare, EdTech, Retail/E-commerce | Cross-industry digital product development |
WeAreBrain vs Reaktor: overview
WeAreBrain
WeAreBrain is a Netherlands-headquartered AI-native product studio founded in 2015, combining AI product development with software modernization, e-commerce integrations, and automation services. It describes itself as 'a winning team, not an agency,' with a 60+ person, 13-nationality team and an average client tenure of 3.8 years, alongside an NPS score above 80 (per company website). Named clients include SidelineSwap and clevergig, which was acquired by Visma.
Reaktor
Reaktor is a Helsinki, Finland digital consultancy founded in 2000, with 700 employees across nine offices including Helsinki, New York, Amsterdam, Stockholm, and Tokyo. It co-created 'Elements of AI,' a free AI-literacy MOOC with the University of Helsinki taken by over half a million people worldwide, and integrates AI and data-driven technology across a broader human-centred design and engineering practice rather than positioning itself as a standalone ML vendor.
Services and capabilities: WeAreBrain vs Reaktor
| Capability | WeAreBrain | Reaktor |
|---|---|---|
| ML Development | ✓ | ✓ |
| AI Consulting | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI | ✓ | ✗ |
| MLOps | ✗ | ✗ |
| Data Engineering | ✗ | ✓ |
| Staff Augmentation | ✗ | ✗ |
Tech stack comparison: WeAreBrain vs Reaktor
| Framework / platform | WeAreBrain | Reaktor |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: WeAreBrain vs Reaktor
| Criterion | WeAreBrain | Reaktor |
|---|---|---|
| Minimum engagement | Not published | Not published (large enterprise engagements) |
| Engagement models | Dedicated team, Fixed project | Dedicated team, Project-based consulting |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / mid-market | Enterprise / mid-market |
Target audience comparison: WeAreBrain vs Reaktor
| Dimension | WeAreBrain | Reaktor |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Transport & Logistics, Healthcare, EdTech | Cross-industry digital product development |
| Best use cases | AI-native product MVP development, E-commerce AI personalization | Human-centred AI product design and development, Enterprise AI literacy training programs |
| Typical project type | Dedicated team | Dedicated team |
WeAreBrain vs Reaktor: pros and cons
| WeAreBrain | |
|---|---|
| + | 80+ NPS and 3.8-year average client tenure signal strong retention (per company website) |
| + | 13-nationality team supports multilingual, multi-market European delivery |
| + | Combines AI-native product development with broader software modernization services |
| + | Founded 2015 with a decade of continuous operation |
| - | Broader software, e-commerce, and automation service lines mean ML is one of several offerings, not the sole focus |
| - | 60+ team size is modest relative to enterprise-scale competitors on this list |
| - | Notable named clients (SidelineSwap, clevergig) are smaller-profile than some competitors' enterprise logos |
| Reaktor | |
|---|---|
| + | 700 employees across nine global offices (Helsinki, New York, Amsterdam, Stockholm, Tokyo, and more) give major delivery scale |
| + | 'Elements of AI' MOOC, with 500,000+ participants, is a uniquely large-scale public AI-education contribution |
| + | Human-centred design integrated directly with AI and data engineering, useful for consumer-facing AI products |
| + | Founded 2000 — a quarter-century of continuous Helsinki-based operation |
| - | AI/ML is one capability within a much broader design-and-engineering digital consultancy, not the firm's primary specialization |
| - | 700-person, nine-office scale trades boutique-level AI focus for broad digital-consultancy breadth |
| - | Public case studies emphasize design and product outcomes more than specific ML model performance metrics |
Who should choose WeAreBrain?
WeAreBrain is the right choice for startups and scale-ups wanting AI-native product development combined with broader software modernization, not just an isolated ML model..
Frames itself around culture and retention — 'a winning team, not an agency' — with a long average client tenure as central to its pitch alongside technical delivery.. Minimum engagement starts at Not published. Works best with clients in Transport & Logistics, Healthcare, EdTech, Retail/E-commerce.
Who should choose Reaktor?
Reaktor is the right choice for enterprises wanting AI capability embedded within a broader human-centred digital product and design consultancy, rather than a standalone ML vendor..
Co-created 'Elements of AI,' a free AI literacy MOOC with the University of Helsinki taken by over half a million people worldwide — a public-education contribution unmatched by any other company on this list.. Minimum engagement starts at Not published (large enterprise engagements). Works best with clients in Cross-industry digital product development.
Decision matrix: WeAreBrain vs Reaktor
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | WeAreBrain |
| You need a large dedicated team for an ongoing programme | WeAreBrain |
| Your budget is at the lower end | Compare: WeAreBrain (Not published) vs Reaktor (Not published (large enterprise engagements)) |
| You need specialist depth in a specific vertical | WeAreBrain |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | WeAreBrain |
Use case fit: WeAreBrain vs Reaktor
| Use case | WeAreBrain fit | Reaktor fit | Winner |
|---|---|---|---|
| AI-native product MVP development | Strong | Limited | WeAreBrain |
| E-commerce AI personalization | Strong | Limited | WeAreBrain |
| Human-centred AI product design and development | Limited | Strong | Reaktor |
| Enterprise AI literacy training programs | Limited | Strong | Reaktor |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: WeAreBrain vs Reaktor
WeAreBrain (4.3/5) is the stronger overall choice for most Machine Learning Development projects. Frames itself around culture and retention — 'a winning team, not an agency' — with a long average client tenure as central to its pitch alongside technical delivery.. It is best for startups and scale-ups wanting AI-native product development combined with broader software modernization, not just an isolated ML model..
Reaktor (3.8/5) is the better choice when enterprises wanting AI capability embedded within a broader human-centred digital product and design consultancy, rather than a standalone ML vendor.. If your situation matches those criteria, Reaktor is a competitive option.
Related comparisons
WeAreBrain vs Reaktor FAQ
Is WeAreBrain better than Reaktor?
WeAreBrain (4.3/5) scores higher overall, but "better" depends on your use case. WeAreBrain is better for startups and scale-ups wanting AI-native product development combined with broader software modernization, not just an isolated ML model.. Reaktor is better for enterprises wanting AI capability embedded within a broader human-centred digital product and design consultancy, rather than a standalone ML vendor..
How do WeAreBrain and Reaktor differ in pricing?
WeAreBrain uses dedicated team, fixed project pricing with a minimum engagement of Not published. Reaktor uses dedicated team, project-based consulting pricing with a minimum engagement of Not published (large enterprise engagements). Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: WeAreBrain or Reaktor?
Reaktor 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 WeAreBrain and Reaktor?
WeAreBrain's primary differentiator is: frames itself around culture and retention — 'a winning team, not an agency' — with a long average client tenure as central to its pitch alongside technical delivery.. Reaktor's primary differentiator is: co-created 'elements of ai,' a free ai literacy mooc with the university of helsinki taken by over half a million people worldwide — a public-education contribution unmatched by any other company on this list.. They also differ in team size (60+ vs 700), minimum engagement (Not published vs Not published (large enterprise engagements)), and primary industries served (Transport & Logistics, Healthcare vs Cross-industry digital product development).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.