Vstorm vs Endava: full comparison for 2026
Quick verdict
Vstorm (4.5/5) edges ahead of Endava (3.3/5) overall. Vstorm is the better choice for mid-market and enterprise buyers wanting boutique advisory with named enterprise references. Endava is the stronger option for enterprises wanting a publicly traded UK-headquartered technology consultancy for AI advisory. The right choice depends on your project size, budget, and required tech stack.
Vstorm vs Endava: head-to-head summary
| Criterion | Vstorm | Endava |
|---|---|---|
| Founded | 2017 | 2000 |
| HQ | Wrocław, Poland | London, UK |
| Team size | 11-50 | 11225 |
| Rating | 4.5 / 5 | 3.3 / 5 |
| Best for | Mid-market and enterprise buyers wanting boutique advisory with named enterprise references | Enterprises wanting a publicly traded UK-headquartered technology consultancy for AI advisory |
| Pricing model | Fixed project, retainer | Retainer, dedicated team, T&M |
| Min. engagement | $20K | $100K |
| Primary tech stack | LangChain, LlamaIndex, Pinecone | AWS, Azure, Kubernetes |
| Industries served | Automotive, Manufacturing, SaaS | Fintech, Retail, Telecom |
Vstorm vs Endava: overview
Vstorm
Vstorm is a boutique AI agent-engineering consultancy launched in 2017 and based in Wrocław, Poland, with additional presence in Berlin and Amsterdam. The team of roughly two dozen specializes in advising on and building custom agentic and retrieval-augmented generation (RAG) automation for clients including Mercedes-Benz, Intel, and Synera.
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: Vstorm vs Endava
| Capability | Vstorm | Endava |
|---|---|---|
| Enterprise automation | ✗ | ✓ |
| Agent orchestration | ✗ | ✗ |
| RAG & knowledge agents | ✓ | ✗ |
| Data & analytics agents | ✗ | ✗ |
| LLM integration | ✓ | ✗ |
| Workflow integration | ✗ | ✓ |
Tech stack comparison: Vstorm vs Endava
| Framework / platform | Vstorm | Endava |
|---|---|---|
| LangChain | ✓ | N/A |
| LangGraph | N/A | N/A |
| AutoGen | N/A | N/A |
| LlamaIndex | ✓ | N/A |
| OpenAI | ✓ | N/A |
| Anthropic Claude | ✓ | N/A |
| Pinecone | ✓ | N/A |
| AWS | N/A | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | ✓ |
Pricing comparison: Vstorm vs Endava
| Criterion | Vstorm | Endava |
|---|---|---|
| Minimum engagement | $20K | $100K |
| Engagement models | Fixed project, Retainer | Retainer, Dedicated team, T&M |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Vstorm vs Endava
| Dimension | Vstorm | Endava |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Automotive, Manufacturing, SaaS | Fintech, Retail, Telecom |
| Best use cases | Agentic RAG advisory and delivery, Automation strategy for manufacturing/automotive | Enterprise AI technology consulting, Large-scale systems architecture advisory |
| Typical project type | Fixed project | Retainer |
Vstorm vs Endava: pros and cons
| Vstorm | |
|---|---|
| + | Named enterprise clients (Mercedes-Benz, Intel) validate advisory quality |
| + | Deep RAG and agentic-automation specialization, not generalist strategy consulting |
| + | Small team keeps senior-consultant involvement high on every engagement |
| - | Team size (~24) caps how many concurrent advisory engagements it can run |
| - | Limited public case-study detail on longer-term post-implementation support |
| 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 Vstorm?
Vstorm is the right choice for mid-market and enterprise buyers wanting boutique advisory with named enterprise references.
Verified enterprise client roster (Mercedes-Benz, Intel) despite a small advisory team. Minimum engagement starts at $20K. Works best with clients in Automotive, Manufacturing, SaaS.
Who should choose Endava?
Endava is the right choice for enterprises wanting a publicly traded UK-headquartered technology consultancy for AI advisory.
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: Vstorm vs Endava
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Vstorm |
| You need a large dedicated team for an ongoing programme | Endava |
| Your budget is at the lower end | Vstorm |
| You need specialist depth in a specific vertical | Vstorm |
| 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: Vstorm vs Endava
| Use case | Vstorm fit | Endava fit | Winner |
|---|---|---|---|
| Agentic RAG advisory and delivery | Strong | Limited | Vstorm |
| Automation strategy for manufacturing/automotive | Strong | Limited | Vstorm |
| Enterprise AI technology consulting | Limited | Strong | Endava |
| Large-scale systems architecture advisory | Limited | Strong | Endava |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Vstorm vs Endava
Vstorm (4.5/5) is the stronger overall choice for most AI Agent projects. Verified enterprise client roster (Mercedes-Benz, Intel) despite a small advisory team. It is best for mid-market and enterprise buyers wanting boutique advisory with named enterprise references.
Endava (3.3/5) is the better choice when enterprises wanting a publicly traded UK-headquartered technology consultancy for AI advisory. If your situation matches those criteria, Endava is a competitive option.
Related comparisons
Vstorm vs Endava FAQ
Is Vstorm better than Endava?
Vstorm (4.5/5) scores higher overall, but "better" depends on your use case. Vstorm is better for mid-market and enterprise buyers wanting boutique advisory with named enterprise references. Endava is better for enterprises wanting a publicly traded UK-headquartered technology consultancy for AI advisory.
How do Vstorm and Endava differ in pricing?
Vstorm uses fixed project, retainer pricing with a minimum engagement of $20K. 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: Vstorm or Endava?
Endava 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 Vstorm and Endava?
Vstorm's primary differentiator is: verified enterprise client roster (mercedes-benz, intel) despite a small advisory team. 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 (11-50 vs 11225), minimum engagement ($20K vs $100K), and primary industries served (Automotive, Manufacturing vs Fintech, Retail).