WeAreBrain vs Grape Up: full comparison for 2026
Last updated: July 2026
Quick verdict
WeAreBrain (4.3/5) edges ahead of Grape Up (4.0/5) 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.. Grape Up is the stronger option for automotive and finance enterprises wanting agentic AI and generative-AI-powered legacy modernization delivered by an experienced cloud-native engineering firm.. The right choice depends on your project size, budget, and required tech stack.
WeAreBrain vs Grape Up: head-to-head summary
| Criterion | WeAreBrain | Grape Up |
|---|---|---|
| Founded | 2015 | 2006 |
| HQ | Netherlands (internationally distributed team) | Kraków, Poland |
| Team size | 60+ | Not disclosed |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Best for | Startups and scale-ups wanting AI-native product development combined with broader software modernization, not just an isolated ML model. | Automotive and finance enterprises wanting agentic AI and generative-AI-powered legacy modernization delivered by an experienced cloud-native engineering firm. |
| Pricing model | Dedicated team, fixed project | Fixed project, dedicated team |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, AI product tooling, Shopify/SAP Commerce Cloud integrations | Python, Kubernetes, Cloud-native platforms |
| Industries served | Transport & Logistics, Healthcare, EdTech, Retail/E-commerce | Automotive, Financial Services, Manufacturing, Aviation |
WeAreBrain vs Grape Up: 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.
Grape Up
Grape Up is a Kraków, Poland AI and cloud-native engineering firm founded in 2006, delivering agentic AI, generative-AI-powered legacy modernization, and advanced analytics alongside its own productized platforms: Databoostr for data sharing and monetization, and Cloudboostr, a Kubernetes stack for cloud deployment. Named clients include Porsche, Nissan, Mazda, Ducati, BNP, and Allstate (per company website), concentrated in automotive, finance, manufacturing, and aviation.
Services and capabilities: WeAreBrain vs Grape Up
| Capability | WeAreBrain | Grape Up |
|---|---|---|
| ML Development | ✓ | ✗ |
| AI Consulting | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| MLOps | ✗ | ✓ |
| Data Engineering | ✗ | ✗ |
| Staff Augmentation | ✗ | ✗ |
Tech stack comparison: WeAreBrain vs Grape Up
| Framework / platform | WeAreBrain | Grape Up |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | ✓ |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: WeAreBrain vs Grape Up
| Criterion | WeAreBrain | Grape Up |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated team, Fixed project | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / mid-market | Enterprise / mid-market |
Target audience comparison: WeAreBrain vs Grape Up
| Dimension | WeAreBrain | Grape Up |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Transport & Logistics, Healthcare, EdTech | Automotive, Financial Services, Manufacturing |
| Best use cases | AI-native product MVP development, E-commerce AI personalization | Agentic AI workflow automation for enterprises, Generative-AI-powered legacy system modernization |
| Typical project type | Dedicated team | Fixed project |
WeAreBrain vs Grape Up: 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 |
| Grape Up | |
|---|---|
| + | Notable automotive and finance client roster (Porsche, Nissan, Mazda, Ducati, BNP, Allstate) per company website |
| + | Own productized platforms (Databoostr, Cloudboostr) show deeper platform-engineering capability than pure staffing vendors |
| + | Founded 2006 — nearly two decades of continuous Kraków-based delivery |
| + | Agentic AI and GenAI-powered legacy modernization address a current enterprise pain point directly |
| - | Team size and detailed employee count are not publicly disclosed |
| - | Cloud-native and Kubernetes engineering roots mean AI/ML depth may be shallower than pure-play ML boutiques |
| - | Public case studies emphasize client logos over specific project outcomes and 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 Grape Up?
Grape Up is the right choice for automotive and finance enterprises wanting agentic AI and generative-AI-powered legacy modernization delivered by an experienced cloud-native engineering firm..
Built its own productized platforms (Databoostr, Cloudboostr) alongside custom delivery — a hybrid product-plus-services model less common among pure consultancies on this list.. Minimum engagement starts at Not published. Works best with clients in Automotive, Financial Services, Manufacturing, Aviation.
Decision matrix: WeAreBrain vs Grape Up
| 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 Grape Up (Not published) |
| 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 Grape Up
| Use case | WeAreBrain fit | Grape Up fit | Winner |
|---|---|---|---|
| AI-native product MVP development | Strong | Limited | WeAreBrain |
| E-commerce AI personalization | Strong | Limited | WeAreBrain |
| Agentic AI workflow automation for enterprises | Limited | Strong | Grape Up |
| Generative-AI-powered legacy system modernization | Limited | Strong | Grape Up |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: WeAreBrain vs Grape Up
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..
Grape Up (4.0/5) is the better choice when automotive and finance enterprises wanting agentic AI and generative-AI-powered legacy modernization delivered by an experienced cloud-native engineering firm.. If your situation matches those criteria, Grape Up is a competitive option.
Related comparisons
WeAreBrain vs Grape Up FAQ
Is WeAreBrain better than Grape Up?
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.. Grape Up is better for automotive and finance enterprises wanting agentic AI and generative-AI-powered legacy modernization delivered by an experienced cloud-native engineering firm..
How do WeAreBrain and Grape Up differ in pricing?
WeAreBrain uses dedicated team, fixed project pricing with a minimum engagement of Not published. Grape Up uses fixed project, dedicated team pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: WeAreBrain or Grape Up?
WeAreBrain 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 Grape Up?
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.. Grape Up's primary differentiator is: built its own productized platforms (databoostr, cloudboostr) alongside custom delivery — a hybrid product-plus-services model less common among pure consultancies on this list.. They also differ in team size (60+ vs Not disclosed), minimum engagement (Not published vs Not published), and primary industries served (Transport & Logistics, Healthcare vs Automotive, Financial Services).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.