Best Machine Learning Development Companies in Europe

Twistag vs DEPT: full comparison for 2026

Last updated: July 2026

Quick verdict

Twistag (4.5/5) edges ahead of DEPT (4.0/5) overall. Twistag is the better choice for growth-stage and enterprise brands needing senior-engineer-only AI agent and data platform builds. 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.

Twistag vs DEPT: head-to-head summary

Criterion Twistag DEPT
Founded 2016 2015
HQ Lisbon, Portugal Amsterdam, Netherlands
Team size 11–50 1000+
Rating 4.5 / 5 4.0 / 5
Best for Growth-stage and enterprise brands needing senior-engineer-only AI agent and data platform builds Large enterprise brands needing ML-driven marketing personalization at global scale
Pricing model Fixed project, dedicated team Retainer, dedicated team
Min. engagement $25K $75K
Primary tech stack Python, LangChain, AWS Python, GCP, AWS
Industries served Retail, Automotive, Pharmaceuticals, Logistics, Enterprise Retail, Media, Enterprise, E-commerce

Twistag vs DEPT: overview

Twistag

Twistag is a Lisbon, Portugal-headquartered AI and product engineering agency founded in 2016. The team of roughly 50 senior engineers builds AI agents, data platforms, and cloud-native products, with named clients including Nike, Volkswagen, Autodesk, Sanofi, and Glovo (per company website; independently unverifiable at the project-detail level). Twistag positions itself around senior-engineer-only delivery rather than junior-staffed teams.

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: Twistag vs DEPT

Capability Twistag DEPT
ML model development
Computer vision
NLP
Generative AI / LLM integration
MLOps
AI strategy consulting
Staff augmentation

Tech stack comparison: Twistag vs DEPT

Framework / platform Twistag DEPT
Python
TensorFlow N/A
PyTorch N/A N/A
AWS
Azure N/A N/A
Kubernetes N/A

Pricing comparison: Twistag vs DEPT

Criterion Twistag 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: Twistag vs DEPT

Dimension Twistag DEPT
Best company size Startup to mid-market Startup to mid-market
Best industries Retail, Automotive, Pharmaceuticals Retail, Media, Enterprise
Best use cases Building production AI agents for customer operations, Standing up a cloud-native data platform ML-driven marketing personalization at global brand scale, Enterprise data engineering supporting a large media or retail platform
Typical project type Fixed project Retainer

Twistag vs DEPT: pros and cons

Twistag
+ Client roster includes well-known global brands, cited on the company website
+ Senior-only staffing model, no junior-developer training-ground approach
+ Nearly a decade of operating history since founding in 2016 in Lisbon's growing tech hub
+ Combines AI agent development with broader data platform and cloud-native engineering
- Named enterprise client work is per company website and not independently verifiable at the project level
- Smaller team (11–50) may create capacity constraints for very large multi-year 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 Twistag?

Twistag is the right choice for growth-stage and enterprise brands needing senior-engineer-only AI agent and data platform builds.

Senior-only engineering team with a client roster including well-known global brands. Minimum engagement starts at $25K. Works best with clients in Retail, Automotive, Pharmaceuticals, Logistics, Enterprise.

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: Twistag vs DEPT

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Twistag
You need a large dedicated team for an ongoing programme Twistag
Your budget is at the lower end Twistag
You need specialist depth in a specific vertical Twistag
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build Twistag

Use case fit: Twistag vs DEPT

Use case Twistag fit DEPT fit Winner
Building production AI agents for customer operations Strong Limited Twistag
Standing up a cloud-native data platform Strong Limited Twistag
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: Twistag vs DEPT

Twistag (4.5/5) is the stronger overall choice for most Machine Learning Development projects. Senior-only engineering team with a client roster including well-known global brands. It is best for growth-stage and enterprise brands needing senior-engineer-only AI agent and data platform builds.

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

Twistag vs DEPT FAQ

Is Twistag better than DEPT?

Twistag (4.5/5) scores higher overall, but "better" depends on your use case. Twistag is better for growth-stage and enterprise brands needing senior-engineer-only AI agent and data platform builds. DEPT is better for large enterprise brands needing ML-driven marketing personalization at global scale.

How do Twistag and DEPT differ in pricing?

Twistag 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: Twistag or DEPT?

Twistag 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 Twistag and DEPT?

Twistag's primary differentiator is: senior-only engineering team with a client roster including well-known global brands. 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 ($25K vs $75K), and primary industries served (Retail, Automotive vs Retail, Media).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.