Capgemini
Paris-based global integrator that bought WNS to add AI-run business operations
What is Capgemini?
Capgemini was founded in Grenoble in 1967, is headquartered in Paris, and employs more than 340,000 people. In October 2025 it completed its acquisition of WNS, adding business process services that it plans to run with AI agents. Production AI here is usually part of a large program that includes process redesign and outsourced operations. It's a strong fit for European multinationals and a poor one for a single pilot.
Capgemini works primarily with clients in Financial services, Manufacturing, Public sector, Retail, Energy & utilities sectors. Its primary differentiator is: Production AI bundled with outsourced business operations after the WNS deal.
Capgemini tech stack and services
| Service area |
|---|
| Pilot to Production |
| Managed Run After Launch |
| Agentic AI |
| CRM / ERP Integration |
| Microsoft Partner |
Capgemini pricing
Short answer: Capgemini prices its work as follows: program fees and managed services; rates not published. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Time & materials | Hourly; see pricing model above | Scope that will change as you learn |
| Managed services | Monthly fee; not public | Running and monitoring live systems |
Capgemini pros and cons
| Advantages | Things to consider |
|---|---|
| +Can run AI-assisted business operations as a managed service | -WNS integration (completed October 2025) is still in progress |
| +Wide European footprint | -Not set up for small, fast pilots |
| +Deep SAP and enterprise platform experience | -Rates not published |
Capgemini vs alternatives
How Capgemini compares to the other top AI Implementation providers.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Teams whose AI pilot works but can't ship. | Model gateway with routing, provider fallback, and regression tests, released through a canary rollout | 4.8 | Full comparison |
| Provectus | AWS shops taking GenAI pilots to production. | AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker | 4.6 | Full comparison |
| Grid Dynamics | Enterprises moving several AI pilots to production. | Forward-deployed engineers working from ready-made GAIN platforms for agentic and retail AI | 4.5 | Full comparison |
| deepsense.ai | Teams that need measured accuracy before launch. | Evaluation-first engineering that proves accuracy on your data before release | 4.5 | Full comparison |
| Neurons Lab | Banks and insurers shipping AI on AWS. | Financial-services AI built inside existing compliance controls on AWS | 4.4 | Full comparison |
| Datatonic | Google Cloud users needing MLOps and managed run. | Vertex AI MLOps with a managed service to run models after launch | 4.4 | Full comparison |
| Quantiphi | Large document and contact-center AI programs. | Large Google Cloud and AWS engineering bench for document and speech AI in production | 4.3 | Full comparison |
| ML6 | European firms needing EU-compliant production AI. | European AI engineering with EU AI Act and GDPR requirements built into delivery | 4.3 | Full comparison |
| Thoughtworks | Engineering orgs wanting disciplined AI delivery. | Continuous delivery practice applied to models and prompts, with tool views published in its Technology Radar | 4.3 | Full comparison |
| N-iX | Mid-size and large firms wanting nearshore MLOps. | Dedicated MLOps practice backed by a large nearshore engineering bench | 4.2 | Full comparison |
| DS Stream | Teams wanting packaged LLMOps at nearshore rates. | Packaged LLMOps setup with evaluation, prompt versioning, guardrails, and model routing | 4.2 | Full comparison |
| Addepto | Mid-size firms wanting tested LLM apps cheaply. | Open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point | 4.2 | Full comparison |
| RTS Labs | US mid-market firms on a small budget. | The lowest entry point on this page, with a committed ship date for production code | 4.1 | Full comparison |
| EPAM Systems | Enterprises adding AI across many products. | Engineering capacity to put AI into dozens of products under one program | 4.1 | Full comparison |
| Accenture | Multinationals rolling AI out across many countries. | Staffing and compliance depth to run production AI in many countries at once | 4.1 | Full comparison |
| Winder.ai | Teams needing senior MLOps advice and review. | Senior MLOps expertise from a recognized author, at boutique scale | 4.0 | Full comparison |
| NineTwoThree AI Studio | Funded companies launching an AI product. | Product design and engineering together for customer-facing AI launches | 4.0 | Full comparison |
| Globant | US firms wanting nearshore AI engineering. | Nearshore Latin American engineering teams in US time zones | 4.0 | Full comparison |
| SoftServe | Existing clients extending engineering into AI. | Google Cloud Premier engineering firm with an MLOps and generative AI practice | 4.0 | Full comparison |
| InData Labs | Mid-size firms with one focused AI project. | Discovery, proof of concept, and production build from a small data science team | 3.9 | Full comparison |
| Instinctools | Palantir users building agentic workflows. | Palantir Foundry and AIP implementation alongside custom software engineering | 3.9 | Full comparison |
| Netguru | Product teams adding AI features to apps. | AI features shipped as part of web and mobile product work | 3.9 | Full comparison |
| STX Next | Python teams needing extra AI engineers. | Python engineering depth for AI that lives inside your codebase | 3.9 | Full comparison |
| 10Clouds | Smaller banks and lenders adding AI. | A dedicated financial-institutions AI unit with its own AIConsole platform | 3.8 | Full comparison |
| LeewayHertz | Buyers wanting a platform-based AI build. | Builds on its own ZBrain platform, now backed by The Hackett Group | 3.7 | Full comparison |
Capgemini FAQ
What is Capgemini?
Paris-based global integrator that bought WNS to add AI-run business operations
How much does Capgemini charge?
Pricing model: program fees and managed services; rates not published. Minimum engagement is not publicly disclosed. A discovery call is required to get project-specific quotes.
What tech stack does Capgemini use?
Capgemini works with Azure, AWS, Google Cloud, SAP, Salesforce. Primary industries served include Financial services, Manufacturing, Public sector, Retail, Energy & utilities.
Is Capgemini right for enterprise?
Best for: european multinationals pairing AI with outsourcing. Team size: 340,000+. Key consideration: WNS integration (completed October 2025) is still in progress.
What are the best Capgemini alternatives?
The best alternatives to Capgemini depend on your use case. Top options are:
- Tensorway: model gateway with routing, provider fallback, and regression tests, released through a canary rollout
- Provectus: AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker
- Grid Dynamics: forward-deployed engineers working from ready-made GAIN platforms for agentic and retail AI
Compare Capgemini with other AI Implementation providers
Verify all details directly with Capgemini before making a decision.