Tooploox vs DEPT: full comparison for 2026
Quick verdict
Tooploox (4.3/5) edges ahead of DEPT (4.0/5) overall. Tooploox is the better choice for hard ML/AI research-engineering problems. DEPT is the stronger option for large brands, ML-driven marketing personalization at scale. The right choice depends on your project size, budget, and required tech stack.
Tooploox vs DEPT: head-to-head summary
| Criterion | Tooploox | DEPT |
|---|---|---|
| Founded | 2012 | 2015 |
| HQ | Wroclaw, Poland | Amsterdam, Netherlands |
| Team size | 51–200 | 1000+ |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Primary differentiator | Research-grade ML engineering with peer-reviewed academic recognition at ECCV 2024, alongside client delivery | 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 |
| Pricing model | Fixed project, dedicated team | Retainer, dedicated team |
| Min. engagement | $25K | $75K |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, GCP, AWS |
| Industries served | Healthcare, Enterprise, Media, SaaS | Retail, Media, Enterprise, E-commerce |
Tooploox vs DEPT: overview
Tooploox
Tooploox, founded in 2012 and based in Wroclaw and Warsaw, Poland, is an engineering company that specifically takes on projects where AI and machine learning represent the core technical challenge, rather than treating ML as a secondary feature. Its portfolio includes a digital histopathology platform and a neural network technique (MagMax) recognized at ECCV 2024. Tooploox was named Top AI Company in Poland and Top Machine Learning Company in Poland for 2025 by Clutch.
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: Tooploox vs DEPT
| Capability | Tooploox | DEPT |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✗ | ✓ |
| MLOps | ✗ | ✗ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: Tooploox vs DEPT
| Framework / platform | Tooploox | DEPT |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Tooploox vs DEPT
| Criterion | Tooploox | DEPT |
|---|---|---|
| Minimum engagement | $25K | $75K |
| Engagement models | Fixed project, Dedicated team | Retainer, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Tooploox vs DEPT
| Dimension | Tooploox | DEPT |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Enterprise, Media | Retail, Media, Enterprise |
| Best use cases | Digital histopathology and medical imaging analysis, Novel neural network architecture research and development | ML-driven marketing personalization at global brand scale, Enterprise data engineering supporting a large media or retail platform |
| Typical project type | Fixed project | Retainer |
Tooploox vs DEPT: pros and cons
| Tooploox | |
|---|---|
| + | Recognized by Clutch as Top AI Company and Top Machine Learning Company in Poland for 2025 |
| + | Academic-grade research credibility, including a technique presented at ECCV 2024 |
| + | Over a decade of operating history since founding in 2012, focused specifically on hard ML problems |
| + | Domain depth in digital histopathology and healthcare computer vision |
| - | Research-oriented positioning may mean higher cost for simpler, more standard ML integration work |
| - | Mid-size team (51–200) shared across research and delivery work |
| 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 Tooploox?
A typical fit: digital histopathology and medical imaging analysis.
Research-grade ML engineering with peer-reviewed academic recognition at ECCV 2024, alongside client delivery. Minimum engagement starts at $25K. Works best with clients in Healthcare, Enterprise, Media, SaaS.
Who should choose DEPT?
A typical fit: ML-driven marketing personalization at global brand 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: Tooploox vs DEPT
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Tooploox |
| You need a large dedicated team for an ongoing programme | Tooploox |
| Your budget is at the lower end | Tooploox |
| You need specialist depth in a specific vertical | Tooploox |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Tooploox |
Use case fit: Tooploox vs DEPT
| Use case | Tooploox fit | DEPT fit | Winner |
|---|---|---|---|
| Digital histopathology and medical imaging analysis | Strong | Strong | Both equally |
| Novel neural network architecture research and development | Strong | Limited | Tooploox |
| 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: Tooploox vs DEPT
Tooploox (4.3/5) is the stronger overall choice for most Machine Learning Development projects. Research-grade ML engineering with peer-reviewed academic recognition at ECCV 2024, alongside client delivery.
DEPT (4.0/5) is worth a look if you need enterprise data engineering supporting a large media or retail platform. If your situation matches that, DEPT is a competitive option.
Related comparisons
Tooploox vs DEPT FAQ
Is Tooploox better than DEPT?
Tooploox (4.3/5) scores higher overall, but "better" depends on your use case. Tooploox's strongest advantage: recognized by Clutch as Top AI Company and Top Machine Learning Company in Poland for 2025. DEPT's strongest advantage: global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list.
How do Tooploox and DEPT differ in pricing?
Tooploox uses fixed project, dedicated team pricing with a minimum engagement of $25K. 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: Tooploox or DEPT?
Tooploox 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 Tooploox and DEPT?
Tooploox's primary differentiator is: research-grade ML engineering with peer-reviewed academic recognition at ECCV 2024, alongside client delivery. 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 (51–200 vs 1000+), minimum engagement ($25K vs $75K), and primary industries served (Healthcare, Enterprise vs Retail, Media).