Capgemini vs Deviniti: full comparison for 2026
Quick verdict
Capgemini (3.4/5) edges ahead of Deviniti (3.2/5) overall. Capgemini is the better choice for global enterprises wanting a European-headquartered services group with a large committed AI investment. Deviniti is the stronger option for teams already on Atlassian tooling wanting AI agent services integrated into that ecosystem. The right choice depends on your project size, budget, and required tech stack.
Capgemini vs Deviniti: head-to-head summary
| Criterion | Capgemini | Deviniti |
|---|---|---|
| Founded | 1967 | 2004 |
| HQ | Paris, France | Wrocław, Poland |
| Team size | 423400 | 201-250 |
| Rating | 3.4 / 5 | 3.2 / 5 |
| Best for | Global enterprises wanting a European-headquartered services group with a large committed AI investment | Teams already on Atlassian tooling wanting AI agent services integrated into that ecosystem |
| Pricing model | Retainer, dedicated team | Fixed project, dedicated team |
| Min. engagement | $200K | $15K |
| Primary tech stack | AWS, Azure, GCP | AWS, Azure, Python |
| Industries served | Fintech, Manufacturing, Retail, Telecom | SaaS, Manufacturing, Fintech |
Capgemini vs Deviniti: overview
Capgemini
Capgemini was founded on October 1, 1967 and is headquartered in Paris, France, with 423,400 employees as of 2025. The firm announced a €2 billion investment in artificial intelligence over three years, and its global services portfolio includes data and AI solutions across generative AI and quantum computing initiatives.
Deviniti
Deviniti was founded on December 13, 2004 in Wrocław, Poland by Piotr Jan Dorosz and Jacek Michał Machata, and now has 250+ employees. The company combines Atlassian-focused consulting and marketplace apps with custom software development, cloud/DevOps, and AI application services on fixed-project or dedicated-team terms.
Services and capabilities: Capgemini vs Deviniti
| Capability | Capgemini | Deviniti |
|---|---|---|
| Workflow integration | ✗ | ✓ |
| Enterprise automation | ✓ | ✓ |
| Task automation | ✗ | ✓ |
| Agent orchestration | ✗ | ✗ |
| LLM integration | ✓ | ✗ |
| Customer support agents | ✗ | ✗ |
Tech stack comparison: Capgemini vs Deviniti
| Framework / platform | Capgemini | Deviniti |
|---|---|---|
| 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 | ✓ | N/A |
Pricing comparison: Capgemini vs Deviniti
| Criterion | Capgemini | Deviniti |
|---|---|---|
| Minimum engagement | $200K | $15K |
| Engagement models | Retainer, Dedicated team, T&M | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Capgemini vs Deviniti
| Dimension | Capgemini | Deviniti |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Manufacturing, Retail | SaaS, Manufacturing, Fintech |
| Best use cases | Global enterprise AI investment programs, Large-scale data and AI service delivery | Atlassian-integrated workflow agent services, Custom AI application delivery |
| Typical project type | Retainer | Fixed project |
Capgemini vs Deviniti: pros and cons
| Capgemini | |
|---|---|
| + | 58+ years of consulting and technology services history |
| + | Publicly quantified €2B AI investment commitment provides unusual financial transparency |
| + | 423,000+ employees support the largest, most complex global service programs |
| - | Very high minimum engagement puts it out of reach for all but the largest enterprise buyers |
| - | Massive scale means minimal boutique-style senior-partner attention on individual engagements |
| Deviniti | |
|---|---|
| + | 20+ years of operating history with a clear founding date and leadership |
| + | Deep Atlassian ecosystem expertise supports agent service integration into existing workflow tools |
| + | Combines marketplace product development with custom consulting delivery |
| - | Atlassian-ecosystem specialization is a narrower fit for buyers outside that toolchain |
| - | AI application services are a newer addition relative to its two-decade core consulting history |
Who should choose Capgemini?
Capgemini is the right choice for global enterprises wanting a European-headquartered services group with a large committed AI investment.
Publicly announced €2 billion, three-year AI investment commitment — a concrete, quantified financial signal of scale. Minimum engagement starts at $200K. Works best with clients in Fintech, Manufacturing, Retail, Telecom.
Who should choose Deviniti?
Deviniti is the right choice for teams already on Atlassian tooling wanting AI agent services integrated into that ecosystem.
Atlassian marketplace-app pedigree gives it unusually deep workflow-tool integration service experience. Minimum engagement starts at $15K. Works best with clients in SaaS, Manufacturing, Fintech.
Decision matrix: Capgemini vs Deviniti
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Deviniti |
| You need a large dedicated team for an ongoing programme | Capgemini |
| Your budget is at the lower end | Deviniti |
| You need specialist depth in a specific vertical | Capgemini |
| 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: Capgemini vs Deviniti
| Use case | Capgemini fit | Deviniti fit | Winner |
|---|---|---|---|
| Global enterprise AI investment programs | Strong | Limited | Capgemini |
| Large-scale data and AI service delivery | Strong | Limited | Capgemini |
| Atlassian-integrated workflow agent services | Limited | Strong | Deviniti |
| Custom AI application delivery | Limited | Strong | Deviniti |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Capgemini vs Deviniti
Capgemini (3.4/5) is the stronger overall choice for most AI Agent Development projects. Publicly announced €2 billion, three-year AI investment commitment — a concrete, quantified financial signal of scale. It is best for global enterprises wanting a European-headquartered services group with a large committed AI investment.
Deviniti (3.2/5) is the better choice when teams already on Atlassian tooling wanting AI agent services integrated into that ecosystem. If your situation matches those criteria, Deviniti is a competitive option.
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Capgemini vs Deviniti FAQ
Is Capgemini better than Deviniti?
Capgemini (3.4/5) scores higher overall, but "better" depends on your use case. Capgemini is better for global enterprises wanting a European-headquartered services group with a large committed AI investment. Deviniti is better for teams already on Atlassian tooling wanting AI agent services integrated into that ecosystem.
How do Capgemini and Deviniti differ in pricing?
Capgemini uses retainer, dedicated team pricing with a minimum engagement of $200K. Deviniti uses fixed project, dedicated team pricing with a minimum engagement of $15K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Capgemini or Deviniti?
Capgemini is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each provider before shortlisting.
What are the main differences between Capgemini and Deviniti?
Capgemini's primary differentiator is: publicly announced €2 billion, three-year ai investment commitment — a concrete, quantified financial signal of scale. Deviniti's primary differentiator is: atlassian marketplace-app pedigree gives it unusually deep workflow-tool integration service experience. They also differ in team size (423400 vs 201-250), minimum engagement ($200K vs $15K), and primary industries served (Fintech, Manufacturing vs SaaS, Manufacturing).