DEPT
Amsterdam-founded global digital agency with over 4,000 specialists and a proprietary AI marketing platform.
What is 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.
DEPT was founded in 2015 and is headquartered in Amsterdam, Netherlands. The firm employs 1000+ people and works primarily with clients in Retail, Media, Enterprise, E-commerce sectors. Its 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.
DEPT tech stack and services
| Service area |
|---|
| ML Development |
| Data Engineering |
| AI Consulting |
| Generative AI |
DEPT use cases
Short answer: DEPT is best suited for large brands, ML-driven marketing personalization at scale.
| Use case |
|---|
| ML-driven marketing personalization at global brand scale |
| Enterprise data engineering supporting a large media or retail platform |
| Large multi-year, multi-region digital transformation programmes |
| AI-powered growth marketing for an established enterprise brand |
DEPT pricing
Short answer: DEPT uses a retainer, dedicated team pricing approach. Minimum engagement starts at $75K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Retainer | Monthly rate; not public | Ongoing AI engineering |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
DEPT pros and cons
| Advantages | Things to consider |
|---|---|
| +Global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list | -ML and AI sits within a much broader marketing and full-service digital agency offering, not a dedicated ML practice |
| +Proprietary AI-enabled marketing technology platform, Ada, with proven enterprise brand clients | -High minimum engagement size, inaccessible for startups or small businesses |
| +Carlyle Group backing provides financial stability for very large, long-term programmes | -Enterprise agency structure means less specialized, boutique-style ML research depth |
| +Named clients include Google, TikTok, KFC, and eBay, indicating enterprise-grade delivery capacity |
DEPT vs alternatives
How DEPT compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Startups and mid-market, senior dedicated ML team. | a full-stack ML delivery team (data science, MLOps, QA) inherited from an established parent software company, at boutique-agency pricing. | 4.9 | Full comparison |
| ML6 | Enterprises, production MLOps at scale. | Official OpenAI Services Partner status combined with over a decade of pure-play ML engineering focus | 4.7 | Full comparison |
| Alexander Thamm | DACH manufacturers, AI strategy plus ML delivery. | Deep specialization in industrial and automotive ML use cases across the German Mittelstand | 4.6 | Full comparison |
| Kineo.ai | Mid-market EU businesses, lean AI consulting. | All-Germany team of AI consultants focused specifically on operational-efficiency ML use cases | 4.6 | Full comparison |
| DataRoot Labs | Startups and SMBs, lean ML team, competitive rates. | Founder-led, unfunded boutique with nearly a decade of focused custom ML delivery experience | 4.5 | Full comparison |
| Twistag | Growth-stage brands, senior-only AI agent builds. | Senior-only engineering team with a client roster including well-known global brands | 4.5 | Full comparison |
| Preste | EU companies, custom CV/NLP, French presence. | Dual Paris and Kyiv structure pairing French market presence with dedicated computer vision and NLP engineering delivery | 4.4 | Full comparison |
| STX Next | Companies wanting ML plus large-scale Python engineering. | One of Europe's largest dedicated Python engineering companies, with ML and data practices built on that scale | 4.3 | Full comparison |
| Neoteric | Mid-market companies, gen-AI PoC to production. | Two-decade-old Polish software house with a dedicated generative AI practice and a US-facing New York office | 4.3 | Full comparison |
| Tooploox | Hard ML/AI research-engineering problems. | Research-grade ML engineering with peer-reviewed academic recognition at ECCV 2024, alongside client delivery | 4.3 | Full comparison |
| Opinov8 | Enterprises and startups, AI across cloud engineering. | AI treated as a foundational layer across the entire engineering lifecycle, not a bolt-on service | 4.2 | Full comparison |
| FELD M | EU enterprises, long-established multi-country AI consulting. | Over two decades of operating history since founding in 2002, with organic growth into a five-office pan-European practice | 4.2 | Full comparison |
| WeAreBrain | Companies wanting AI within digital product builds. | Digital product agency DNA combined with a dedicated AI, ML, and intelligent automation practice | 4.2 | Full comparison |
| DATAFOREST | Small/mid-market, data engineering plus ML analytics. | Combined data engineering (ETL) and ML analytics practice with a growing review base | 4.1 | Full comparison |
| Probayes | Automotive, defense, finance — Bayesian modeling expertise. | Over two decades of specialization in Bayesian AI and predictive analytics, predating the current ML and AI boom | 4.1 | Full comparison |
| Digica | Regulated industries, ML plus embedded systems. | Combines ML model development with embedded systems and IoT engineering for regulated hardware-adjacent industries | 4.1 | Full comparison |
| Imaginary Cloud | Companies wanting ML plus strong product design. | Design-led software development studio with AI positioned as a first-class capability, not an afterthought | 4.0 | Full comparison |
| N-iX | Enterprises, ML bundled with large-scale engineering. | Over two decades of engineering scale, over 1,000 staff, with an EU-registered legal entity in Malta | 4.0 | Full comparison |
| Gemmo | Companies wanting a structured, staged AI engagement. | Structured three-phase engagement model of Pathfinder, Implementation, and Optimization, rather than an open-ended consulting retainer | 4.0 | Full comparison |
| Plain Concepts | Azure-standardized enterprises, certified Microsoft AI partner. | Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise | 3.9 | Full comparison |
| Edvantis | Enterprises, EU-registered nearshore ML engineering. | EU legal registration in Poland combined with substantial delivery scale across Ukraine and Germany | 3.9 | Full comparison |
| CodeLeap | Early-stage startups, fast founder-friendly AI features. | Founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines | 3.9 | Full comparison |
| High-Tech Systems & Software | Healthcare orgs, AI bundled with healthcare software. | Deep healthcare-sector software specialization in supply chain and telemedicine, with AI and ML layered on top | 3.8 | Full comparison |
| Software Mind | Enterprises, ML bundled with multi-region engineering. | Over 25 years of operating history and enterprise-scale delivery capacity across three continents | 3.8 | Full comparison |
| Innowise | Enterprises, low-cost nearshore staff augmentation with AI. | Very large delivery scale and broad geographic reach, positioned for volume staff augmentation over specialist ML depth | 3.8 | Full comparison |
| BJSS | UK public sector, enterprise-grade AI, proven consultancy. | Over three decades of operating history and deep specialization in regulated, complex enterprise environments | 3.8 | Full comparison |
| Siili Solutions | Nordic/EU enterprises, publicly listed IT consultancy. | Publicly traded on Nasdaq Helsinki, offering financial transparency uncommon among privately held ML firms | 3.7 | Full comparison |
| SDG Group | Large enterprises, ML analytics within BPM programmes. | Three decades of management consulting heritage applied to enterprise-scale analytics and AI programmes | 3.7 | Full comparison |
| Transparity | UK Azure enterprises, certified Microsoft AI partner. | Proprietary AI Factory framework built specifically around Microsoft Azure and Copilot technologies | 3.7 | Full comparison |
DEPT FAQ
What is 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.
How much does DEPT charge?
DEPT uses retainer, dedicated team pricing. Minimum engagement starts at $75K. A discovery call is required to get project-specific quotes.
What tech stack does DEPT use?
DEPT works with Python, GCP, AWS, BigQuery, TensorFlow, React. Primary industries served include Retail, Media, Enterprise, E-commerce.
Is DEPT right for enterprise?
Large brands, ML-driven marketing personalization at scale. 1000+ team size. Key consideration: ML and AI sits within a much broader marketing and full-service digital agency offering, not a dedicated ML practice.
What are the best DEPT alternatives?
The best alternatives to DEPT depend on your use case. Top options are:
- Tensorway: a full-stack ml delivery team (data science, mlops, qa) inherited from an established parent software company, at boutique-agency pricing.
- ML6: official openai services partner status combined with over a decade of pure-play ml engineering focus
- Alexander Thamm: deep specialization in industrial and automotive ml use cases across the german mittelstand