CodeLeap vs DEPT: full comparison for 2026
Last updated: July 2026
Quick verdict
DEPT (4.0/5) edges ahead of CodeLeap (3.9/5) overall. DEPT is the better choice for large enterprise brands needing ML-driven marketing personalization at global scale. CodeLeap is the stronger option for early-stage and growth-stage startups wanting fast, founder-friendly AI feature development. The right choice depends on your project size, budget, and required tech stack.
CodeLeap vs DEPT: head-to-head summary
| Criterion | CodeLeap | DEPT |
|---|---|---|
| Founded | 2019 | 2015 |
| HQ | London, UK | Amsterdam, Netherlands |
| Team size | 11–50 | 1000+ |
| Rating | 3.9 / 5 | 4.0 / 5 |
| Best for | Early-stage and growth-stage startups wanting fast, founder-friendly AI feature development | Large enterprise brands needing ML-driven marketing personalization at global scale |
| Pricing model | Fixed project, dedicated team | Retainer, dedicated team |
| Min. engagement | $15K | $75K |
| Primary tech stack | Python, React, Node.js | Python, GCP, AWS |
| Industries served | SaaS, E-commerce, Fintech | Retail, Media, Enterprise, E-commerce |
CodeLeap vs DEPT: overview
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.
DEPT
DEPT, founded in Amsterdam in 2015, has grown into a global digital agency with over 4,000 digital specialists across more than 30 offices on five continents, backed by the Carlyle Group. DEPT's AI-enabled marketing technology platform, Ada, and its Engineering practice deliver machine learning-driven personalization, growth, and data engineering work for major brands including Google, TikTok, and eBay. As a large, private-equity-backed marketing and engineering agency, ML and AI here sits within a much broader full-service offering rather than being the firm's sole focus.
Services and capabilities: CodeLeap vs DEPT
| Capability | CodeLeap | DEPT |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: CodeLeap vs DEPT
| Framework / platform | CodeLeap | DEPT |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | ✓ |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: CodeLeap vs DEPT
| Criterion | CodeLeap | DEPT |
|---|---|---|
| Minimum engagement | $15K | $75K |
| Engagement models | Fixed project, Dedicated team | Retainer, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: CodeLeap vs DEPT
| Dimension | CodeLeap | DEPT |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, E-commerce, Fintech | Retail, Media, Enterprise |
| Best use cases | Adding an AI feature to an early-stage startup product, Fast MVP development with an embedded ML component | ML-driven marketing personalization at global brand scale, Enterprise data engineering supporting a large media or retail platform |
| Typical project type | Fixed project | Retainer |
CodeLeap vs DEPT: pros and cons
| 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 |
| DEPT | |
|---|---|
| + | Global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list |
| + | Proprietary AI-enabled marketing technology platform, Ada, with proven enterprise brand clients |
| + | Carlyle Group backing provides financial stability for very large, long-term programmes |
| + | Named clients include Google, TikTok, KFC, and eBay, indicating enterprise-grade delivery capacity |
| - | ML and AI sits within a much broader marketing and full-service digital agency offering, not a dedicated ML practice |
| - | High minimum engagement size, inaccessible for startups or small businesses |
| - | Enterprise agency structure means less specialized, boutique-style ML research depth |
Who should choose CodeLeap?
CodeLeap is the right choice for early-stage and growth-stage startups wanting fast, founder-friendly AI feature development.
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.
Who should choose DEPT?
DEPT is the right choice for large enterprise brands needing ML-driven marketing personalization at global scale.
Proprietary AI marketing platform, Ada, and global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list. Minimum engagement starts at $75K. Works best with clients in Retail, Media, Enterprise, E-commerce.
Decision matrix: CodeLeap vs DEPT
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | CodeLeap |
| You need a large dedicated team for an ongoing programme | CodeLeap |
| Your budget is at the lower end | CodeLeap |
| You need specialist depth in a specific vertical | DEPT |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | CodeLeap |
Use case fit: CodeLeap vs DEPT
| Use case | CodeLeap fit | DEPT fit | Winner |
|---|---|---|---|
| Adding an AI feature to an early-stage startup product | Strong | Limited | CodeLeap |
| Fast MVP development with an embedded ML component | Strong | Limited | CodeLeap |
| ML-driven marketing personalization at global brand scale | Limited | Strong | DEPT |
| Enterprise data engineering supporting a large media or retail platform | Limited | Strong | DEPT |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: CodeLeap vs DEPT
DEPT (4.0/5) is the stronger overall choice for most Machine Learning Development projects. Proprietary AI marketing platform, Ada, and global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list. It is best for large enterprise brands needing ML-driven marketing personalization at global scale.
CodeLeap (3.9/5) is the better choice when early-stage and growth-stage startups wanting fast, founder-friendly AI feature development. If your situation matches those criteria, CodeLeap is a competitive option.
Related comparisons
CodeLeap vs DEPT FAQ
Is CodeLeap better than DEPT?
DEPT (4.0/5) scores higher overall, but "better" depends on your use case. CodeLeap is better for early-stage and growth-stage startups wanting fast, founder-friendly AI feature development. DEPT is better for large enterprise brands needing ML-driven marketing personalization at global scale.
How do CodeLeap and DEPT differ in pricing?
CodeLeap uses fixed project, dedicated team pricing with a minimum engagement of $15K. DEPT uses retainer, dedicated team pricing with a minimum engagement of $75K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: CodeLeap or DEPT?
CodeLeap 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 CodeLeap and DEPT?
CodeLeap's primary differentiator is: founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines. DEPT's primary differentiator is: proprietary ai marketing platform, ada, and global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list. They also differ in team size (11–50 vs 1000+), minimum engagement ($15K vs $75K), and primary industries served (SaaS, E-commerce vs Retail, Media).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.