Capgemini vs Infosys: full comparison for 2026
Quick verdict
Capgemini (3.4/5) edges ahead of Infosys (3.1/5) overall. Capgemini is the better choice for global enterprises wanting a European-headquartered services group with a large committed AI investment. Infosys is the stronger option for enterprises wanting a large, named library of pre-built agents backed by a Google Cloud partnership. The right choice depends on your project size, budget, and required tech stack.
Capgemini vs Infosys: head-to-head summary
| Criterion | Capgemini | Infosys |
|---|---|---|
| Founded | 1967 | 1981 |
| HQ | Paris, France | Bangalore, India |
| Team size | 423400 | 300000 |
| Rating | 3.4 / 5 | 3.1 / 5 |
| Best for | Global enterprises wanting a European-headquartered services group with a large committed AI investment | Enterprises wanting a large, named library of pre-built agents backed by a Google Cloud partnership |
| Pricing model | Retainer, dedicated team | Retainer, dedicated team, T&M |
| Min. engagement | $200K | $150K |
| Primary tech stack | AWS, Azure, GCP | GCP, AWS, Azure |
| Industries served | Fintech, Manufacturing, Retail, Telecom | Fintech, Retail, Telecom, Manufacturing |
Capgemini vs Infosys: 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.
Infosys
Infosys was founded in 1981 by seven co-founders including N.R. Narayana Murthy and is headquartered in Bangalore, India, with over 300,000 employees. The firm launched more than 200 enterprise AI agents through its Infosys Topaz AI offerings in partnership with Google Cloud's Vertex AI Platform, and its Agentic Foundry delivers pre-built agents, open frameworks, and responsible AI tools on retainer or dedicated-team terms.
Services and capabilities: Capgemini vs Infosys
| Capability | Capgemini | Infosys |
|---|---|---|
| Workflow integration | ✗ | ✗ |
| Enterprise automation | ✓ | ✓ |
| Task automation | ✗ | ✗ |
| Agent orchestration | ✗ | ✗ |
| LLM integration | ✓ | ✓ |
| Customer support agents | ✗ | ✗ |
Tech stack comparison: Capgemini vs Infosys
| Framework / platform | Capgemini | Infosys |
|---|---|---|
| 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: Capgemini vs Infosys
| Criterion | Capgemini | Infosys |
|---|---|---|
| Minimum engagement | $200K | $150K |
| 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: Capgemini vs Infosys
| Dimension | Capgemini | Infosys |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Manufacturing, Retail | Fintech, Retail, Telecom |
| Best use cases | Global enterprise AI investment programs, Large-scale data and AI service delivery | Pre-built enterprise agent deployment (Topaz), Google Cloud Vertex AI agent integration |
| Typical project type | Retainer | Retainer |
Capgemini vs Infosys: 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 |
| Infosys | |
|---|---|
| + | 45+ years of enterprise IT services history |
| + | 200+ pre-built enterprise agents (Topaz) already launched, backed by a named Google Cloud partnership |
| + | 300,000+ 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 |
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 Infosys?
Infosys is the right choice for enterprises wanting a large, named library of pre-built agents backed by a Google Cloud partnership.
200+ named enterprise AI agents already launched via Topaz, built on Google Cloud's Vertex AI Platform. Minimum engagement starts at $150K. Works best with clients in Fintech, Retail, Telecom, Manufacturing.
Decision matrix: Capgemini vs Infosys
| 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 | Capgemini |
| Your budget is at the lower end | Infosys |
| 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 Infosys
| Use case | Capgemini fit | Infosys fit | Winner |
|---|---|---|---|
| Global enterprise AI investment programs | Strong | Limited | Capgemini |
| Large-scale data and AI service delivery | Strong | Strong | Both equally |
| Pre-built enterprise agent deployment (Topaz) | Limited | Strong | Infosys |
| Google Cloud Vertex AI agent integration | Limited | Strong | Infosys |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Capgemini vs Infosys
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.
Infosys (3.1/5) is the better choice when enterprises wanting a large, named library of pre-built agents backed by a Google Cloud partnership. If your situation matches those criteria, Infosys is a competitive option.
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Capgemini vs Infosys FAQ
Is Capgemini better than Infosys?
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. Infosys is better for enterprises wanting a large, named library of pre-built agents backed by a Google Cloud partnership.
How do Capgemini and Infosys differ in pricing?
Capgemini uses retainer, dedicated team pricing with a minimum engagement of $200K. Infosys uses retainer, dedicated team, t&m pricing with a minimum engagement of $150K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Capgemini or Infosys?
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 Infosys?
Capgemini's primary differentiator is: publicly announced €2 billion, three-year ai investment commitment — a concrete, quantified financial signal of scale. Infosys's primary differentiator is: 200+ named enterprise ai agents already launched via topaz, built on google cloud's vertex ai platform. They also differ in team size (423400 vs 300000), minimum engagement ($200K vs $150K), and primary industries served (Fintech, Manufacturing vs Fintech, Retail).