Deloitte vs 10Clouds: full comparison for 2026
Quick verdict
Deloitte (4.2/5) edges ahead of 10Clouds (3.8/5) overall. Deloitte is the better choice for global enterprises wanting AI strategy from a Big Four name. 10Clouds is the stronger option for product teams wanting AI strategy folded into UX and design. The right choice depends on your project size, budget, and required tech stack.
Deloitte vs 10Clouds: head-to-head summary
| Criterion | Deloitte | 10Clouds |
|---|---|---|
| Founded | 1845 | 2009 |
| HQ | London, United Kingdom | Warsaw, Poland |
| Team size | 470,000 | 51-200 |
| Rating | 4.2 / 5 | 3.8 / 5 |
| Primary differentiator | The largest professional services network in the world, with a dedicated AI Institute | AI advisory treated as one integrated capability inside full product design |
| Pricing model | Retainer, enterprise contracting | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, AWS, Azure | Python, React, Node.js |
| Industries served | Financial services, Healthcare, Manufacturing, Government | Fintech, Healthcare, Retail & e-commerce |
Deloitte vs 10Clouds: overview
Deloitte
Deloitte dates to 1845 in London and has grown into the largest professional services network in the world by both revenue and headcount, employing roughly 470,000 people as of 2025. Its AI and Insights practice spans generative AI, agentic AI, and edge intelligence, and it maintains a dedicated Deloitte AI Institute for research and thought leadership. At this scale, AI advisory is one service line inside an enormous global firm, not a purpose-built boutique agency.
10Clouds
10Clouds has run out of Warsaw, Poland since 2009, with a headcount reported around 176 as of mid-2024 against a wider LinkedIn range of 51-200. The agency's core business is digital product consultancy, web and mobile development, and UX design, with AI advisory treated as an integrated capability rather than a standalone service line.
Services and capabilities: Deloitte vs 10Clouds
| Capability | Deloitte | 10Clouds |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✓ | ✗ |
| Machine learning | ✓ | ✓ |
| Data engineering | ✗ | ✓ |
| MLOps | ✗ | ✗ |
| Fixed-price projects | ✗ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Deloitte vs 10Clouds
| Framework / platform | Deloitte | 10Clouds |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: Deloitte vs 10Clouds
| Criterion | Deloitte | 10Clouds |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Retainer, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Deloitte vs 10Clouds
| Dimension | Deloitte | 10Clouds |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Healthcare, Manufacturing | Fintech, Healthcare, Retail & e-commerce |
| Best use cases | Running an enterprise AI strategy engagement that needs Big Four brand credibility., Bundling AI advisory into an existing audit, tax, or broader advisory relationship. | Getting AI strategy input at the same time a product's UX gets redesigned., Adding AI advisory to an existing web or mobile product roadmap. |
| Typical project type | Retainer | Fixed project |
Deloitte vs 10Clouds: pros and cons
| Deloitte | |
|---|---|
| + | Scale at 470,000 people makes it the largest professional services network in the world. |
| + | A dedicated Deloitte AI Institute adds published research behind the advisory work. |
| + | Almost two centuries of institutional history and enterprise relationships. |
| + | Covers generative AI, agentic AI, and edge intelligence under one named practice. |
| - | AI advisory is one service line inside an enormous, diversified professional services firm |
| - | Big Four pricing and minimum engagement sizes exclude most small and mid-size buyers |
| 10Clouds | |
|---|---|
| + | A strong product design and UX practice means AI strategy recommendations arrive with real implementation context. |
| + | Fifteen-plus years of operating history in the Warsaw tech scene. |
| + | Comfortable across the full product stack, not just the AI layer. |
| + | A mid-size team keeps senior engineers involved on most engagements. |
| - | AI advisory sits alongside, not ahead of, the agency's core product design business |
| - | Less AI-specific case-study depth than agencies built around AI from founding |
Who should choose Deloitte?
A typical fit: running an enterprise AI strategy engagement that needs Big Four brand credibility.
The largest professional services network in the world, with a dedicated AI Institute. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Manufacturing, Government.
Who should choose 10Clouds?
A typical fit: getting AI strategy input at the same time a product's UX gets redesigned.
AI advisory treated as one integrated capability inside full product design. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Healthcare, Retail & e-commerce.
Decision matrix: Deloitte vs 10Clouds
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | 10Clouds |
| You need a large dedicated team for an ongoing programme | Deloitte |
| Your budget is at the lower end | Compare: Deloitte (Not disclosed) vs 10Clouds (Not disclosed) |
| You need specialist depth in a specific vertical | Deloitte |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Deloitte |
Use case fit: Deloitte vs 10Clouds
| Use case | Deloitte fit | 10Clouds fit | Winner |
|---|---|---|---|
| Running an enterprise AI strategy engagement that needs Big Four brand credibility. | Strong | Strong | Both equally |
| Bundling AI advisory into an existing audit, tax, or broader advisory relationship. | Strong | Limited | Deloitte |
| Getting AI strategy input at the same time a product's UX gets redesigned. | Limited | Strong | 10Clouds |
| Adding AI advisory to an existing web or mobile product roadmap. | Limited | Strong | 10Clouds |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: Deloitte vs 10Clouds
Deloitte (4.2/5) is the stronger overall choice for most AI Consulting projects. The largest professional services network in the world, with a dedicated AI Institute.
10Clouds (3.8/5) is worth a look if you need adding AI advisory to an existing web or mobile product roadmap. If your situation matches that, 10Clouds is a competitive option.
Related comparisons
Deloitte vs 10Clouds FAQ
Is Deloitte better than 10Clouds?
Deloitte (4.2/5) scores higher overall, but "better" depends on your use case. Deloitte's strongest advantage: scale at 470,000 people makes it the largest professional services network in the world. 10Clouds's strongest advantage: a strong product design and UX practice means AI strategy recommendations arrive with real implementation context.
How do Deloitte and 10Clouds differ in pricing?
Deloitte uses retainer, enterprise contracting pricing. 10Clouds uses fixed project or dedicated team pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Deloitte or 10Clouds?
Deloitte 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 Deloitte and 10Clouds?
Deloitte's primary differentiator is: the largest professional services network in the world, with a dedicated AI Institute. 10Clouds's primary differentiator is: AI advisory treated as one integrated capability inside full product design. They also differ in team size (470,000 vs 51-200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Fintech, Healthcare).
Verify all details directly with each agency before making a decision.