Tensorway vs Transparity: full comparison for 2026
Quick verdict
Tensorway (4.9/5) edges ahead of Transparity (3.7/5) overall. Tensorway is the better choice for startups and mid-market, senior dedicated ML team. Transparity is the stronger option for UK Azure enterprises, certified Microsoft AI partner. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs Transparity: head-to-head summary
| Criterion | Tensorway | Transparity |
|---|---|---|
| Founded | 2019 | 2015 |
| HQ | Alicante, Spain | United Kingdom |
| Team size | 50+ | 201–500 |
| Rating | 4.9 / 5 | 3.7 / 5 |
| Primary differentiator | a full-stack ML delivery team (data science, MLOps, QA) inherited from an established parent software company, at boutique-agency pricing | Proprietary AI Factory framework built specifically around Microsoft Azure and Copilot technologies |
| Pricing model | Dedicated team, fixed project, retainer, time and materials | Retainer, fixed project, dedicated team |
| Min. engagement | $10K | $30K |
| Primary tech stack | Python, TensorFlow, PyTorch | Azure ML, Azure OpenAI Service, Power BI |
| Industries served | SaaS, Legal Tech, E-commerce, Healthcare, Financial Services | Insurance, Financial Services, Enterprise, Public Sector |
Tensorway vs Transparity: 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.
Transparity
Transparity, founded in 2015 by David Jobbins and Colin Macandrew, is a UK-headquartered Microsoft pureplay technology partner with around 289 employees. The company delivers AI and machine learning transformation primarily through Microsoft Azure and Copilot technologies via its proprietary AI Factory framework, as demonstrated in its Bordereaux Sync project built with Charles Taylor InsureTech.
Services and capabilities: Tensorway vs Transparity
| Capability | Tensorway | Transparity |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP | ✓ | ✗ |
| Generative AI / LLM integration | ✓ | ✗ |
| MLOps | ✓ | ✓ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✓ | ✗ |
Tech stack comparison: Tensorway vs Transparity
| Framework / platform | Tensorway | Transparity |
|---|---|---|
| Python | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | N/A |
| Azure | ✓ | ✓ |
| Kubernetes | ✓ | N/A |
Pricing comparison: Tensorway vs Transparity
| Criterion | Tensorway | Transparity |
|---|---|---|
| Minimum engagement | $10K | $30K |
| Engagement models | Dedicated team, Fixed project, Retainer, Time and materials, Staff augmentation | Retainer, Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Tensorway vs Transparity
| Dimension | Tensorway | Transparity |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Legal Tech, E-commerce | Insurance, Financial Services, Enterprise |
| Best use cases | Building a production computer vision pipeline for document processing, Deploying a customer-facing AI chatbot or LLM-integrated agent | Azure-native AI transformation for an insurance or financial services client, Microsoft Copilot deployment across enterprise workflows |
| Typical project type | Dedicated team | Retainer |
Tensorway vs Transparity: 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 |
| Transparity | |
|---|---|
| + | Deep Microsoft pureplay partnership status with a proprietary AI Factory delivery framework |
| + | Demonstrated production case study, Bordereaux Sync, built with Charles Taylor InsureTech |
| + | A decade of operating history since founding in 2015, with a growing UK enterprise client base |
| + | Strong fit for insurance and financial services clients needing Azure-based compliance |
| - | Azure-exclusive positioning is a poor fit for clients on AWS, GCP, or open-source ML stacks |
| - | AI and ML transformation is delivered through a broader Microsoft cloud consulting practice rather than as a standalone ML specialization |
| - | Smaller named public case study base than larger, longer-established firms on this list |
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 Transparity?
A typical fit: azure-native AI transformation for an insurance or financial services client.
Proprietary AI Factory framework built specifically around Microsoft Azure and Copilot technologies. Minimum engagement starts at $30K. Works best with clients in Insurance, Financial Services, Enterprise, Public Sector.
Decision matrix: Tensorway vs Transparity
| 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 Transparity
| Use case | Tensorway fit | Transparity 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 AI transformation for an insurance or financial services client | Limited | Strong | Transparity |
| Microsoft Copilot deployment across enterprise workflows | Limited | Strong | Transparity |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Tensorway vs Transparity
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.
Transparity (3.7/5) is worth a look if you need microsoft Copilot deployment across enterprise workflows. If your situation matches that, Transparity is a competitive option.
Related comparisons
Tensorway vs Transparity FAQ
Is Tensorway better than Transparity?
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. Transparity's strongest advantage: deep Microsoft pureplay partnership status with a proprietary AI Factory delivery framework.
How do Tensorway and Transparity differ in pricing?
Tensorway uses dedicated team, fixed project, retainer, time and materials pricing with a minimum engagement of $10K. Transparity uses retainer, fixed project, dedicated team pricing with a minimum engagement of $30K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Tensorway or Transparity?
Transparity 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 Transparity?
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. Transparity's primary differentiator is: proprietary AI Factory framework built specifically around Microsoft Azure and Copilot technologies. They also differ in team size (50+ vs 201–500), minimum engagement ($10K vs $30K), and primary industries served (SaaS, Legal Tech vs Insurance, Financial Services).