Tensorway vs Keyrus: full comparison for 2026
Last updated: July 2026
Quick verdict
Tensorway (4.8/5) edges ahead of Keyrus (3.8/5) overall. Tensorway is the better choice for mid-market teams needing custom ML builds with full production ownership, from model design to drift monitoring. Keyrus is the stronger option for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs Keyrus: head-to-head summary
| Criterion | Tensorway | Keyrus |
|---|---|---|
| Founded | 2007 | 2000 |
| HQ | Kharkiv, Ukraine (US office) | Paris, France |
| Team size | 250+ | 3,500+ |
| Rating | 4.8 / 5 | 3.8 / 5 |
| Best for | Mid-market teams needing custom ML builds with full production ownership, from model design to drift monitoring | International enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience |
| Pricing model | Fixed project, T&M, retainer | T&M, retainer |
| Min. engagement | $15K | $50K+ |
| Primary tech stack | Python, scikit-learn, XGBoost | Python, Tableau, Power BI |
| Industries served | e-commerce, logistics, fintech, healthcare, travel | financial, retail, healthcare, manufacturing, media |
Tensorway vs Keyrus: overview
Tensorway
Tensorway is a machine learning engineering firm with roots in Anadea, a software development company founded in 2001, operating as a dedicated ML-focused unit with US and Ukraine offices. The firm specialises in custom ML product builds requiring sustained ownership — covering model design, training infrastructure, MLOps pipelines, and ongoing drift monitoring under one team. Core stack includes Python (scikit-learn, XGBoost, LightGBM), Prophet for time-series, and cloud platforms such as AWS SageMaker and Azure ML. Industries served include e-commerce, logistics, fintech, healthcare, and online travel.
Keyrus
Keyrus is an international consulting group founded in 2000, headquartered in Paris, France, and operating in over 20 countries with 3,500+ professionals. The company positions itself at the intersection of business, data, and AI — helping clients move from experimental AI to industrial-grade ML systems in production. Services span data strategy, BI, analytics, AI testing, and ML deployment. (Employee count and global footprint per Keyrus official website.)
Services and capabilities: Tensorway vs Keyrus
| Capability | Tensorway | Keyrus |
|---|---|---|
| Custom ML build | ✓ | ✗ |
| ML consulting | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP / LLM | ✓ | ✗ |
| Predictive analytics | ✓ | ✓ |
| MLOps | ✓ | ✓ |
| Data engineering | ✗ | ✓ |
| Generative AI | ✗ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Fixed-price projects | ✓ | ✗ |
| Dedicated team model | ✗ | ✓ |
Tech stack comparison: Tensorway vs Keyrus
| Framework / platform | Tensorway | Keyrus |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS SageMaker | ✓ | N/A |
| Azure ML | ✓ | N/A |
Pricing comparison: Tensorway vs Keyrus
| Criterion | Tensorway | Keyrus |
|---|---|---|
| Minimum engagement | $15K | $50K+ |
| Engagement models | Fixed project, T&M, Retainer | T&M, Retainer, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Tensorway vs Keyrus
| Dimension | Tensorway | Keyrus |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | e-commerce, logistics, fintech | financial, retail, healthcare |
| Best use cases | Time-series demand forecasting for e-commerce or logistics, Fraud detection model for fintech | Industrial AI deployment at enterprise scale, Analytics and ML platform for financial services |
| Typical project type | Fixed project | T&M |
Tensorway vs Keyrus: pros and cons
| Tensorway | |
|---|---|
| + | Full ML lifecycle covered — from scoping to production drift monitoring |
| + | No-handoff model: same team from prototype to deployment |
| + | Strong time-series and predictive analytics specialisation (Prophet, XGBoost) |
| + | Cloud-agnostic: proven on AWS SageMaker and Azure ML |
| + | Flexible engagement: fixed, T&M, or retainer available |
| - | Smaller team than enterprise firms — less suited to Fortune 500 governance requirements |
| - | Non-ML software outside the ML pipeline may need a separate vendor |
| Keyrus | |
|---|---|
| + | Global footprint: 20+ countries, 3,500+ professionals |
| + | Industrial-AI focus — moves clients from PoC to production scale |
| + | Strong analytics and BI alongside ML for full data stack coverage |
| + | AI testing and validation capability |
| - | Large-firm pricing not suited to startup or SMB budgets |
| - | AI is one offering within broader data consulting — not ML-first |
Who should choose Tensorway?
Tensorway is the right choice for mid-market teams needing custom ML builds with full production ownership, from model design to drift monitoring.
Full-lifecycle ML ownership — model design, training infrastructure, and drift monitoring in one team. Minimum engagement starts at $15K. Works best with clients in e-commerce, logistics, fintech, healthcare, travel.
Who should choose Keyrus?
Keyrus is the right choice for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience.
From experimental AI to industrial AI — consulting group specialising in productionising ML for large organisations. Minimum engagement starts at $50K+. Works best with clients in financial, retail, healthcare, manufacturing, media.
Decision matrix: Tensorway vs Keyrus
| 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 | Keyrus |
| 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 | Tensorway |
Use case fit: Tensorway vs Keyrus
| Use case | Tensorway fit | Keyrus fit | Winner |
|---|---|---|---|
| Time-series demand forecasting for e-commerce or logistics | Strong | Limited | Tensorway |
| Fraud detection model for fintech | Strong | Limited | Tensorway |
| Industrial AI deployment at enterprise scale | Limited | Strong | Keyrus |
| Analytics and ML platform for financial services | Limited | Strong | Keyrus |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Tensorway vs Keyrus
Tensorway (4.8/5) is the stronger overall choice for most Machine Learning projects. Full-lifecycle ML ownership — model design, training infrastructure, and drift monitoring in one team. It is best for mid-market teams needing custom ML builds with full production ownership, from model design to drift monitoring.
Keyrus (3.8/5) is the better choice when international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. If your situation matches those criteria, Keyrus is a competitive option.
Related comparisons
Tensorway vs Keyrus FAQ
Is Tensorway better than Keyrus?
Tensorway (4.8/5) scores higher overall, but "better" depends on your use case. Tensorway is better for mid-market teams needing custom ML builds with full production ownership, from model design to drift monitoring. Keyrus is better for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience.
How do Tensorway and Keyrus differ in pricing?
Tensorway uses fixed project, t&m, retainer pricing with a minimum engagement of $15K. Keyrus uses t&m, retainer pricing with a minimum engagement of $50K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Tensorway or Keyrus?
Keyrus is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Tensorway and Keyrus?
Tensorway's primary differentiator is: full-lifecycle ml ownership — model design, training infrastructure, and drift monitoring in one team. Keyrus's primary differentiator is: from experimental ai to industrial ai — consulting group specialising in productionising ml for large organisations. They also differ in team size (250+ vs 3,500+), minimum engagement ($15K vs $50K+), and primary industries served (e-commerce, logistics vs financial, retail).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.