Tensorway vs DEPT: full comparison for 2026
Last updated: July 2026
Quick verdict
Tensorway (4.9/5) edges ahead of DEPT (4.0/5) overall. Tensorway is the better choice for startups and mid-market companies needing a dedicated, senior ML team without enterprise-agency overhead. DEPT is the stronger option for large enterprise brands needing ML-driven marketing personalization at global scale. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs DEPT: head-to-head summary
| Criterion | Tensorway | DEPT |
|---|---|---|
| Founded | 2019 | 2015 |
| HQ | Alicante, Spain | Amsterdam, Netherlands |
| Team size | 11–50 | 1000+ |
| Rating | 4.9 / 5 | 4.0 / 5 |
| Best for | Startups and mid-market companies needing a dedicated, senior ML team without enterprise-agency overhead | Large enterprise brands needing ML-driven marketing personalization at global scale |
| Pricing model | Fixed-price PoC, Time & Material, Dedicated Team, MVP Development | Retainer, dedicated team |
| Min. engagement | $15K | $75K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, GCP, AWS |
| Industries served | SaaS, Legal Tech, E-commerce, Healthcare, Financial Services | Retail, Media, Enterprise, E-commerce |
Tensorway vs DEPT: overview
Tensorway
Tensorway is a Spain-headquartered machine learning and AI development company spun out of Anadea, a 25-year-old software engineering firm. The team of roughly 30 dedicated data scientists, AI engineers, and MLOps specialists delivers custom ML models, computer vision, NLP, and generative AI systems for clients across Europe and the US. Tensorway inherits Anadea's delivery infrastructure and hiring pipeline, giving it more engineering depth than most boutiques its size (15+ delivered ML projects per company website; independently unverifiable). As a relatively young standalone brand founded in 2019, its own market track record is shorter than its parent company's.
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: Tensorway vs DEPT
| Capability | Tensorway | DEPT |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP | ✓ | ✗ |
| Generative AI / LLM integration | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| AI strategy consulting | ✗ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: Tensorway vs DEPT
| Framework / platform | Tensorway | DEPT |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Tensorway vs DEPT
| Criterion | Tensorway | DEPT |
|---|---|---|
| Minimum engagement | $15K | $75K |
| Engagement models | Fixed project, Dedicated team, Time and materials, MVP development | Retainer, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Tensorway vs DEPT
| Dimension | Tensorway | DEPT |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Legal Tech, E-commerce | Retail, Media, Enterprise |
| Best use cases | Building a production computer vision pipeline for document processing, Deploying a customer-facing AI chatbot or LLM-integrated agent | ML-driven marketing personalization at global brand scale, Enterprise data engineering supporting a large media or retail platform |
| Typical project type | Fixed project | Retainer |
Tensorway vs DEPT: pros and cons
| Tensorway | |
|---|---|
| + | Full ML delivery stack in-house: data science, MLOps/DevSecOps, and QA under one roof |
| + | Backed by Anadea's 25-year engineering track record and hiring pipeline |
| + | Broad service range from LLM integration to computer vision to predictive analytics |
| + | Flexible engagement models including fixed-price PoC for budget-constrained startups |
| + | Based in the EU (Spain), simplifying GDPR-compliant data handling for European clients |
| - | Young standalone brand (founded 2019) with a shorter independent track record than its 25-year-old parent Anadea |
| - | Public case studies are limited in number relative to larger regional players |
| - | Smaller team size (around 30) means less capacity for very large enterprise programmes |
| 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 Tensorway?
Tensorway is the right choice for startups and mid-market companies needing a dedicated, senior ML team without enterprise-agency overhead.
Full-stack ML delivery team (data science, MLOps, QA) inherited from a 25-year-old parent company, at boutique-agency pricing. Minimum engagement starts at $15K. Works best with clients in SaaS, Legal Tech, E-commerce, Healthcare, Financial Services.
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: Tensorway vs DEPT
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Tensorway |
| You need a large dedicated team for an ongoing programme | Tensorway |
| Your budget is at the lower end | Tensorway |
| You need specialist depth in a specific vertical | Tensorway |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | DEPT |
Use case fit: Tensorway vs DEPT
| Use case | Tensorway fit | DEPT fit | Winner |
|---|---|---|---|
| Building a production computer vision pipeline for document processing | Strong | Limited | Tensorway |
| Deploying a customer-facing AI chatbot or LLM-integrated agent | Strong | Limited | Tensorway |
| 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: Tensorway vs DEPT
Tensorway (4.9/5) is the stronger overall choice for most Machine Learning Development projects. Full-stack ML delivery team (data science, MLOps, QA) inherited from a 25-year-old parent company, at boutique-agency pricing. It is best for startups and mid-market companies needing a dedicated, senior ML team without enterprise-agency overhead.
DEPT (4.0/5) is the better choice when large enterprise brands needing ML-driven marketing personalization at global scale. If your situation matches those criteria, DEPT is a competitive option.
Related comparisons
Tensorway vs DEPT FAQ
Is Tensorway better than DEPT?
Tensorway (4.9/5) scores higher overall, but "better" depends on your use case. Tensorway is better for startups and mid-market companies needing a dedicated, senior ML team without enterprise-agency overhead. DEPT is better for large enterprise brands needing ML-driven marketing personalization at global scale.
How do Tensorway and DEPT differ in pricing?
Tensorway uses fixed-price poc, time & material, dedicated team, mvp development 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: Tensorway or DEPT?
Tensorway 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 Tensorway and DEPT?
Tensorway's primary differentiator is: full-stack ml delivery team (data science, mlops, qa) inherited from a 25-year-old parent company, at boutique-agency pricing. 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, Legal Tech vs Retail, Media).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.