Tensorway vs Plain Concepts: full comparison for 2026
Quick verdict
Tensorway (4.9/5) edges ahead of Plain Concepts (3.9/5) overall. Tensorway is the better choice for startups and mid-market, senior dedicated ML team. Plain Concepts is the stronger option for azure-standardized enterprises, certified Microsoft AI partner. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs Plain Concepts: head-to-head summary
| Criterion | Tensorway | Plain Concepts |
|---|---|---|
| Founded | 2019 | 2006 |
| HQ | Alicante, Spain | Madrid, Spain |
| Team size | 50+ | 201–500 |
| Rating | 4.9 / 5 | 3.9 / 5 |
| Primary differentiator | a full-stack ML delivery team (data science, MLOps, QA) inherited from an established parent software company, at boutique-agency pricing | Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise |
| Pricing model | Dedicated team, fixed project, retainer, time and materials | Dedicated team, fixed project, retainer |
| Min. engagement | $10K | $35K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Azure ML, Azure OpenAI Service |
| Industries served | SaaS, Legal Tech, E-commerce, Healthcare, Financial Services | Enterprise, Retail, Healthcare, Financial Services |
Tensorway vs Plain Concepts: overview
Tensorway
Tensorway is a Spain-headquartered machine learning and AI development company spun out of its parent software engineering firm. The team of roughly 50 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 its parent'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.
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.
Services and capabilities: Tensorway vs Plain Concepts
| Capability | Tensorway | Plain Concepts |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP | ✓ | ✗ |
| Generative AI / LLM integration | ✓ | ✗ |
| MLOps | ✓ | ✓ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✓ | ✗ |
Tech stack comparison: Tensorway vs Plain Concepts
| Framework / platform | Tensorway | Plain Concepts |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | N/A |
| Azure | ✓ | ✓ |
| Kubernetes | ✓ | ✓ |
Pricing comparison: Tensorway vs Plain Concepts
| Criterion | Tensorway | Plain Concepts |
|---|---|---|
| Minimum engagement | $10K | $35K |
| Engagement models | Dedicated team, Fixed project, Retainer, Time and materials, Staff augmentation | Dedicated team, Fixed project, Retainer |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Tensorway vs Plain Concepts
| Dimension | Tensorway | Plain Concepts |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Legal Tech, E-commerce | Enterprise, Retail, Healthcare |
| Best use cases | Building a production computer vision pipeline for document processing, Deploying a customer-facing AI chatbot or LLM-integrated agent | Azure-native ML model deployment for an enterprise client, Mixed reality plus AI product development |
| Typical project type | Dedicated team | Dedicated team |
Tensorway vs Plain Concepts: pros and cons
| Tensorway | |
|---|---|
| + | Full ML delivery stack in-house: data science, MLOps/DevSecOps, and QA under one roof |
| + | Backed by parent company's 25-year engineering track record and hiring pipeline |
| + | Established project-management and QA processes for predictable, well-documented delivery |
| + | 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 company |
| - | Public case studies are limited in number relative to larger regional players |
| - | Smaller team size (around 50) means less capacity for very large enterprise programmes |
| 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 |
Who should choose Tensorway?
A typical fit: building a production computer vision pipeline for document processing.
a full-stack ML delivery team (data science, MLOps, QA) inherited from an established parent software company, at boutique-agency pricing. Minimum engagement starts at $10K. Works best with clients in SaaS, Legal Tech, E-commerce, Healthcare, Financial Services.
Who should choose Plain Concepts?
A typical fit: azure-native ML model deployment for an enterprise client.
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.
Decision matrix: Tensorway vs Plain Concepts
| 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 | Tensorway |
| You need consulting before committing to a build | Tensorway |
Use case fit: Tensorway vs Plain Concepts
| Use case | Tensorway fit | Plain Concepts 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 |
| Azure-native ML model deployment for an enterprise client | Limited | Strong | Plain Concepts |
| Mixed reality plus AI product development | Limited | Strong | Plain Concepts |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Tensorway vs Plain Concepts
Tensorway (4.9/5) is the stronger overall choice for most Machine Learning Development projects. a full-stack ML delivery team (data science, MLOps, QA) inherited from an established parent software company, at boutique-agency pricing.
Plain Concepts (3.9/5) is worth a look if you need mixed reality plus AI product development. If your situation matches that, Plain Concepts is a competitive option.
Related comparisons
Tensorway vs Plain Concepts FAQ
Is Tensorway better than Plain Concepts?
Tensorway (4.9/5) scores higher overall, but "better" depends on your use case. Tensorway's strongest advantage: full ML delivery stack in-house: data science, MLOps/DevSecOps, and QA under one roof. Plain Concepts's strongest advantage: two decades of operating history since founding in 2006, with Microsoft Gold and AI Partner status.
How do Tensorway and Plain Concepts differ in pricing?
Tensorway uses dedicated team, fixed project, retainer, time and materials pricing with a minimum engagement of $10K. Plain Concepts uses dedicated team, fixed project, retainer pricing with a minimum engagement of $35K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Tensorway or Plain Concepts?
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 Tensorway and Plain Concepts?
Tensorway's primary differentiator is: a full-stack ML delivery team (data science, MLOps, QA) inherited from an established parent software company, at boutique-agency pricing. 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. They also differ in team size (50+ vs 201–500), minimum engagement ($10K vs $35K), and primary industries served (SaaS, Legal Tech vs Enterprise, Retail).