Plain Concepts vs DEPT: full comparison for 2026
Last updated: July 2026
Quick verdict
DEPT (4.0/5) edges ahead of Plain Concepts (3.9/5) overall. DEPT is the better choice for large enterprise brands needing ML-driven marketing personalization at global scale. Plain Concepts is the stronger option for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. The right choice depends on your project size, budget, and required tech stack.
Plain Concepts vs DEPT: head-to-head summary
| Criterion | Plain Concepts | DEPT |
|---|---|---|
| Founded | 2006 | 2015 |
| HQ | Madrid, Spain | Amsterdam, Netherlands |
| Team size | 201–500 | 1000+ |
| Rating | 3.9 / 5 | 4.0 / 5 |
| Best for | Enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery | Large enterprise brands needing ML-driven marketing personalization at global scale |
| Pricing model | Dedicated team, fixed project, retainer | Retainer, dedicated team |
| Min. engagement | $35K | $75K |
| Primary tech stack | Python, Azure ML, Azure OpenAI Service | Python, GCP, AWS |
| Industries served | Enterprise, Retail, Healthcare, Financial Services | Retail, Media, Enterprise, E-commerce |
Plain Concepts vs DEPT: overview
Plain Concepts
Plain Concepts, founded in 2006 and headquartered in Madrid, Spain, is a 450-plus person technology consultancy with offices across the USA, UK, Spain, Germany, the Netherlands, and Romania. As a Microsoft Gold Partner, Microsoft AI Partner, and 2016 Microsoft Partner of the Year, Plain Concepts brings deep Azure-native AI and machine learning delivery experience alongside mixed reality and IoT engineering.
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: Plain Concepts vs DEPT
| Capability | Plain Concepts | DEPT |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✗ | ✓ |
| MLOps | ✓ | ✗ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: Plain Concepts vs DEPT
| Framework / platform | Plain Concepts | DEPT |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | ✓ |
| PyTorch | N/A | N/A |
| AWS | N/A | ✓ |
| Azure | ✓ | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Plain Concepts vs DEPT
| Criterion | Plain Concepts | DEPT |
|---|---|---|
| Minimum engagement | $35K | $75K |
| Engagement models | Dedicated team, Fixed project, Retainer | Retainer, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Plain Concepts vs DEPT
| Dimension | Plain Concepts | DEPT |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Enterprise, Retail, Healthcare | Retail, Media, Enterprise |
| Best use cases | Azure-native ML model deployment for an enterprise client, Mixed reality plus AI product development | ML-driven marketing personalization at global brand scale, Enterprise data engineering supporting a large media or retail platform |
| Typical project type | Dedicated team | Retainer |
Plain Concepts vs DEPT: pros and cons
| Plain Concepts | |
|---|---|
| + | Two decades of operating history since founding in 2006, with Microsoft Gold and AI Partner status |
| + | Multi-country office footprint across Spain, the UK, Germany, the Netherlands, Romania, and the US for broad coverage |
| + | Deep Azure-native ML and AI delivery credentials, useful for Microsoft-standardized enterprises |
| + | Recognized with Microsoft Partner of the Year award in 2016 |
| - | Azure-centric specialization may be less ideal for clients standardized on AWS or GCP |
| - | Broader technology consultancy scope, including mixed reality and IoT, means ML is one of several core practices |
| - | Larger enterprise-oriented engagement sizes, less accessible for very small startup budgets |
| 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 Plain Concepts?
Plain Concepts is the right choice for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery.
Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise. Minimum engagement starts at $35K. Works best with clients in Enterprise, Retail, 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: Plain Concepts vs DEPT
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Plain Concepts |
| You need a large dedicated team for an ongoing programme | Plain Concepts |
| Your budget is at the lower end | Plain Concepts |
| You need specialist depth in a specific vertical | Plain Concepts |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Plain Concepts |
Use case fit: Plain Concepts vs DEPT
| Use case | Plain Concepts fit | DEPT fit | Winner |
|---|---|---|---|
| Azure-native ML model deployment for an enterprise client | Strong | Limited | Plain Concepts |
| Mixed reality plus AI product development | Strong | Limited | Plain Concepts |
| ML-driven marketing personalization at global brand scale | Limited | Strong | DEPT |
| Enterprise data engineering supporting a large media or retail platform | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Plain Concepts 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.
Plain Concepts (3.9/5) is the better choice when enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. If your situation matches those criteria, Plain Concepts is a competitive option.
Related comparisons
Plain Concepts vs DEPT FAQ
Is Plain Concepts better than DEPT?
DEPT (4.0/5) scores higher overall, but "better" depends on your use case. Plain Concepts is better for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. DEPT is better for large enterprise brands needing ML-driven marketing personalization at global scale.
How do Plain Concepts and DEPT differ in pricing?
Plain Concepts uses dedicated team, fixed project, retainer pricing with a minimum engagement of $35K. 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: Plain Concepts or DEPT?
Plain Concepts 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 Plain Concepts and DEPT?
Plain Concepts's primary differentiator is: deep azure-native ai and ml delivery credentials as a microsoft gold and ai partner, plus mixed reality expertise. 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 (201–500 vs 1000+), minimum engagement ($35K vs $75K), and primary industries served (Enterprise, Retail vs Retail, Media).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.