Capgemini group and AWS expand strategic collaboration to enable broad enterprise generative AI adoption

Paris, January 16, 2024 – Capgemini today announced the signing of a multi-year strategic collaboration agreement with AWS, designed to accelerate the adoption of generative AI solutions and technologies amongst organizations of all sizes. Through this collaboration, Capgemini and AWS are focused on helping clients realize the business value of adopting generative AI, while navigating challenges including cost, scale, and trust. It will enable joint clients to move their investments from individual pilots and proof of concepts to production at scale, by leveraging Capgemini’s existing network of AWS Centers of Excellence (CoEs). This expanded collaboration will also accelerate the deployment of innovative industry-specific and functional use cases using Amazon Bedrock to access a range of secure, high-performing foundational models, including Amazon Titan.

Helping clients realize the full value of generative AI at scale

As part of this new initiative, Capgemini and AWS will build industry specific solutions, assets and accelerators supported by a unique platform designed to help clients improve the Total Cost of Ownership (TCO). The new platform optimizes large language models (LLMs) provided as part of Amazon Bedrock to help enable clients to achieve the best generative AI production costs.

Expansion of Capgemini’s AWS Centers of Excellence

As part of this extended collaboration, Capgemini will expand its existing network of AWS CoEs and will train 30,000 employees over the next 3 years across AWS’s advanced technologies, as part of the company’s €2 billion investment in Artificial Intelligence. The global network of Capgemini’s AWS CoEs allows clients to leverage Capgemini’s capabilities in data, AI and cloud to unlock the vast potential of generative AI, enable rapid prototyping of new business scenarios, foster innovation, and navigate the next era of digital transformation.

“With generative AI presenting new opportunities to accelerate innovation, it’s imperative for clients to be able to scale their AI implementations quickly to drive tangible value, optimize investments, and meet the specific needs of their own industry,” said Jerome Simeon, Head of Global Industries and Group Executive Board member at Capgemini. “Capgemini’s deep expertise in data and AI and strong portfolio tailored for industries, together with AWS’s proven methodologies and technologies that help organizations scale their transition to the cloud, will enable joint clients to move from pilot to production at extreme scale, while also helping them optimize their investments and address their sustainability goals. All are vital components in the journey to a digital and sustainable economy.”

Swami Sivasubramanian, Vice President of Data and AI at AWS said, “This expanded partnership with Capgemini will further democratize access to generative AI by empowering organizations to leverage AWS’s industry-leading models and capabilities, like Amazon Bedrock and Amazon Q, to ignite innovation and transform their business. Fueled by massive amounts of enterprise data and human intelligence, joint clients will be able to build and scale generative AI applications that are customized to their business, with privacy and security at the core.”

The partnership expansion comprises several dedicated initiatives to maximize value delivered for clients including:

• Industry solutions – customized, AI-infused capabilities for specific industries
  Leverages Capgemini’s deep industry expertise and AWS’s secure, highly customizable, AI to deliver value across multiple industries, for example:
  • Aerospace: enhanced Lifecycle Optimization for Aerospace platform with additional capabilities from Amazon Bedrock to improve the image recognition and analysis of aviation parts, and assist in the curation of publishing available inventory.  
  • Automotive: AI-enriched capabilities to enable the transformation of the Automotive industry including trusted vehicles, driving automation, customer intimacy as well as supply chain optimization.
  • Financial Services: use cases across banking and capital markets such as customer experience, administration processing, audit, and risk. Leveraging generative AI in the insurance market to enhance policy servicing and claim handling.
• New platform to enable high value business outcomes and optimize TCO
  This strategic collaboration with AWS incorporates a unique methodology and accelerators developed bydata and AI experts at Capgemini. Using LLM cascading and prompt tuning[1] can more efficiently deliver working solutions that combine the client’s own data and data from a range of LLMs available through Amazon Bedrock. In this way, multiple Proof of Concepts (PoCs) can be developed, tested, and deployed at speed while reducing compute. This new approach is designed to create tangible value for clients that can then be channeled into the business to accelerate innovation and enable organizations to explore a greater number of generative AI use cases at scale. By reducing the compute required for implementation, there is also an opportunity to reduce the carbon intensity of generative AI projects.
• Generative AI for Software engineering
  Amazon CodeWhisperer and Amazon Bedrock will be incorporated into Capgemini’s digital cloud platform that provides industry solutions and accelerators to enable clients’ cloud-driven transformations. This will improve efficiency and quality across the entire software life cycle from user story creation through to test case development and execution, with a focus on accelerating development, code conversion, reduction of technical debt, and enhancing the security posture of the developed software.

As a result of their long-term strategic partnership, Capgemini was recently recognized for its global leadership in AI with the coveted AWS Global Partner of the Year 2023 for Artificial Intelligence and Machine Learning (AI/ML), along with six additional awards across global and local categories. Capgemini was singled out in the AI/ML category for the development of the Lifecycle Optimization for Aerospace platform, built on AWS’s Cloud and AI services, that aims todigitalize and automate aircraft records history to improve lifecycle management and enhance parts’ reuse.

“Circular economy is an important axis of our sustainability roadmap, as we successfully repair and reuse many components from both in service or retired aircraft,” says Vincent Etchebehere, VP Sustainability and new mobilities at Air France. “The technologies tested in the platform are very promising and should allow us to increase even further the reuse ratio. As an airline and an MRO[2], we act as a catalyst in our supply chain by selecting the most responsible and sustainable products available.” 

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[1] Prompt tuning involves leveraging a smaller scale model to adapt an input prompt to make it more effective and efficient on the target large language model

[2] MRO: Maintenance, Repair, and Overhaul