Xebia vs Endava: full comparison for 2026
Quick verdict
Xebia (3.9/5) edges ahead of Endava (3.3/5) overall. Xebia is the better choice for enterprises wanting AI advisory plus internal training. Endava is the stronger option for enterprises wanting a publicly-traded UK consultancy for AI advisory. The right choice depends on your project size, budget, and required tech stack.
Xebia vs Endava: head-to-head summary
| Criterion | Xebia | Endava |
|---|---|---|
| Founded | 2001 | 2000 |
| HQ | Atlanta, GA, USA | London, UK |
| Team size | 4501-6735 | 11225 |
| Rating | 3.9 / 5 | 3.3 / 5 |
| Primary differentiator | Combines AI-first advisory with a formal training arm, useful for buyers who need internal capability building alongside delivery | Publicly traded (NYSE: DAVA) with a UK headquarters, useful for EU/UK-anchored enterprise buyers |
| Pricing model | Retainer, dedicated team | Retainer, dedicated team, T&M |
| Min. engagement | $50K | $100K |
| Primary tech stack | AWS, Azure, GCP | AWS, Azure, Kubernetes |
| Industries served | Fintech, Retail, Manufacturing | Fintech, Retail, Telecom |
Xebia vs Endava: overview
Xebia
Xebia began in the Netherlands in 2001 and moved its global headquarters to Atlanta, Georgia in 2023, with employee counts reported between roughly 4,500 and 6,735 depending on source. The firm is an AI-first consulting, software engineering, and training company helping organizations translate AI strategy into production-ready solutions.
Endava
Endava was founded in 2000 by John Cotterell in London and is headquartered there, with 11,225 total employees. The company is a publicly traded (NYSE: DAVA) technology services firm offering strategy consulting, data insights, systems architecture, automation, software engineering, cloud computing, and AI technology consulting.
Services and capabilities: Xebia vs Endava
| Capability | Xebia | Endava |
|---|---|---|
| Enterprise automation | ✓ | ✓ |
| Agent orchestration | ✓ | ✗ |
| RAG & knowledge agents | ✗ | ✗ |
| Data & analytics agents | ✗ | ✗ |
| LLM integration | ✗ | ✗ |
| Workflow integration | ✓ | ✓ |
Tech stack comparison: Xebia vs Endava
| Framework / platform | Xebia | Endava |
|---|---|---|
| LangChain | N/A | N/A |
| LangGraph | N/A | N/A |
| AutoGen | N/A | N/A |
| LlamaIndex | N/A | N/A |
| OpenAI | N/A | N/A |
| Anthropic Claude | N/A | N/A |
| Pinecone | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Kubernetes | ✓ | ✓ |
Pricing comparison: Xebia vs Endava
| Criterion | Xebia | Endava |
|---|---|---|
| Minimum engagement | $50K | $100K |
| Engagement models | Retainer, Dedicated team, T&M | Retainer, Dedicated team, T&M |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Xebia vs Endava
| Dimension | Xebia | Endava |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Retail, Manufacturing | Fintech, Retail, Telecom |
| Best use cases | AI-first transformation advisory, Internal AI capability training | Enterprise AI technology consulting, Large-scale systems architecture advisory |
| Typical project type | Retainer | Retainer |
Xebia vs Endava: pros and cons
| Xebia | |
|---|---|
| + | 23+ years of engineering-consulting history, with an explicit AI-first repositioning |
| + | Dedicated training practice supports internal capability building, not just external delivery |
| + | Large, multi-thousand-person bench supports substantial enterprise programs |
| - | Reported employee counts vary meaningfully across sources (4,500 to 6,735) — confirm scope directly |
| - | Large-firm structure means less boutique-style senior-partner attention on smaller engagements |
| Endava | |
|---|---|
| + | Publicly traded (NYSE: DAVA) with audited financial transparency |
| + | 25+ years of technology consulting history spanning strategy through delivery |
| + | UK headquarters simplifies engagement for European enterprise buyers |
| - | Large-firm structure means less boutique-style senior-partner attention on smaller engagements |
| - | High minimum engagement puts it out of reach for smaller buyers |
Who should choose Xebia?
A typical fit: AI-first transformation advisory.
Combines AI-first advisory with a formal training arm, useful for buyers who need internal capability building alongside delivery. Minimum engagement starts at $50K. Works best with clients in Fintech, Retail, Manufacturing.
Who should choose Endava?
A typical fit: enterprise AI technology consulting.
Publicly traded (NYSE: DAVA) with a UK headquarters, useful for EU/UK-anchored enterprise buyers. Minimum engagement starts at $100K. Works best with clients in Fintech, Retail, Telecom.
Decision matrix: Xebia vs Endava
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | Xebia |
| Your budget is at the lower end | Xebia |
| You need specialist depth in a specific vertical | Xebia |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: Xebia vs Endava
| Use case | Xebia fit | Endava fit | Winner |
|---|---|---|---|
| AI-first transformation advisory | Strong | Limited | Xebia |
| Internal AI capability training | Strong | Limited | Xebia |
| Enterprise AI technology consulting | Strong | Strong | Both equally |
| Large-scale systems architecture advisory | Limited | Strong | Endava |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Xebia vs Endava
Xebia (3.9/5) is the stronger overall choice for most AI Agent projects. Combines AI-first advisory with a formal training arm, useful for buyers who need internal capability building alongside delivery.
Endava (3.3/5) is worth a look if you need large-scale systems architecture advisory. If your situation matches that, Endava is a competitive option.
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Xebia vs Endava FAQ
Is Xebia better than Endava?
Xebia (3.9/5) scores higher overall, but "better" depends on your use case. Xebia's strongest advantage: 23+ years of engineering-consulting history, with an explicit AI-first repositioning. Endava's strongest advantage: publicly traded (NYSE: DAVA) with audited financial transparency.
How do Xebia and Endava differ in pricing?
Xebia uses retainer, dedicated team pricing with a minimum engagement of $50K. Endava uses retainer, dedicated team, t&m pricing with a minimum engagement of $100K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Xebia or Endava?
Xebia is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each consultancy before shortlisting.
What are the main differences between Xebia and Endava?
Xebia's primary differentiator is: combines AI-first advisory with a formal training arm, useful for buyers who need internal capability building alongside delivery. Endava's primary differentiator is: publicly traded (NYSE: DAVA) with a UK headquarters, useful for EU/UK-anchored enterprise buyers. They also differ in team size (4501-6735 vs 11225), minimum engagement ($50K vs $100K), and primary industries served (Fintech, Retail vs Fintech, Retail).