WeAreBrain vs CodeLeap: full comparison for 2026
Quick verdict
WeAreBrain (4.2/5) edges ahead of CodeLeap (3.9/5) overall. WeAreBrain is the better choice for companies wanting AI within digital product builds. CodeLeap is the stronger option for early-stage startups, fast founder-friendly AI features. The right choice depends on your project size, budget, and required tech stack.
WeAreBrain vs CodeLeap: head-to-head summary
| Criterion | WeAreBrain | CodeLeap |
|---|---|---|
| Founded | 2015 | 2019 |
| HQ | Amsterdam, Netherlands | London, UK |
| Team size | 51–200 | 11–50 |
| Rating | 4.2 / 5 | 3.9 / 5 |
| Primary differentiator | Digital product agency DNA combined with a dedicated AI, ML, and intelligent automation practice | Founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines |
| Pricing model | Fixed project, dedicated team | Fixed project, dedicated team |
| Min. engagement | $25K | $15K |
| Primary tech stack | Python, AWS, Azure | Python, React, Node.js |
| Industries served | SaaS, Fintech, Enterprise, Retail | SaaS, E-commerce, Fintech |
WeAreBrain vs CodeLeap: overview
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.
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: WeAreBrain vs CodeLeap
| Capability | WeAreBrain | CodeLeap |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✗ | ✓ |
| MLOps | ✓ | ✗ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: WeAreBrain vs CodeLeap
| Framework / platform | WeAreBrain | CodeLeap |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: WeAreBrain vs CodeLeap
| Criterion | WeAreBrain | CodeLeap |
|---|---|---|
| Minimum engagement | $25K | $15K |
| Engagement models | Fixed project, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: WeAreBrain vs CodeLeap
| Dimension | WeAreBrain | CodeLeap |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, Enterprise | SaaS, E-commerce, Fintech |
| Best use cases | Building an AI-powered consumer-facing digital product, Intelligent process automation for back-office workflows | Adding an AI feature to an early-stage startup product, Fast MVP development with an embedded ML component |
| Typical project type | Fixed project | Fixed project |
WeAreBrain vs CodeLeap: pros and cons
| 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 |
| 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 WeAreBrain?
A typical fit: building an AI-powered consumer-facing digital product.
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.
Who should choose CodeLeap?
A typical fit: adding an AI feature to an early-stage startup product.
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: WeAreBrain vs CodeLeap
| 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 | CodeLeap |
| 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 CodeLeap
| Use case | WeAreBrain fit | CodeLeap fit | Winner |
|---|---|---|---|
| Building an AI-powered consumer-facing digital product | Strong | Limited | WeAreBrain |
| Intelligent process automation for back-office workflows | Strong | Limited | WeAreBrain |
| 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: WeAreBrain vs CodeLeap
WeAreBrain (4.2/5) is the stronger overall choice for most Machine Learning Development projects. Digital product agency DNA combined with a dedicated AI, ML, and intelligent automation practice.
CodeLeap (3.9/5) is worth a look if you need fast MVP development with an embedded ML component. If your situation matches that, CodeLeap is a competitive option.
Related comparisons
WeAreBrain vs CodeLeap FAQ
Is WeAreBrain better than CodeLeap?
WeAreBrain (4.2/5) scores higher overall, but "better" depends on your use case. WeAreBrain's strongest advantage: a decade of operating history since founding in 2015 as an Amsterdam-based digital product agency. CodeLeap's strongest advantage: legally registered in England with a London-based, client-facing team.
How do WeAreBrain and CodeLeap differ in pricing?
WeAreBrain uses fixed project, dedicated team pricing with a minimum engagement of $25K. 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: WeAreBrain or CodeLeap?
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 CodeLeap?
WeAreBrain's primary differentiator is: digital product agency DNA combined with a dedicated AI, ML, and intelligent automation practice. CodeLeap's primary differentiator is: Founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines. They also differ in team size (51–200 vs 11–50), minimum engagement ($25K vs $15K), and primary industries served (SaaS, Fintech vs SaaS, E-commerce).