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First, assess whether the reference contains any valid content. If the reference contains no valid information, such as a 'page not found' message, then all statements should be considered 'unknown'.
If the reference is valid, for a given statement: if the facts or data it contains can be found entirely or partially within the reference, it is considered 'supported' (data accepts rounding); if all facts and data in the statement cannot be found in the reference, it is considered 'unsupported'.

You should return the result in a JSON list format, where each item in the list contains the statement's index and the judgment result, for example:
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    {
        "idx": 1,
        "result": "supported"
    },
    {
        "idx": 2,
        "result": "unsupported"
    }
]

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<reference>
Capgemini announces ‘augmented engineering’ offerings powered by Gen AI - Capgemini

Capgemini is extending its Gen AI portfolio of services with the launch of engineering and R&D-specific Generative AI (Gen AI) infused solutions for clients to accelerate innovation, streamline engineering and R&D processes with high-level automation, and the ability to unlock new discoveries. As a world leader in engineering and R&D services with deep industry knowledge, and a leading player in the AI market, Capgemini is well positioned to help organizations transform their engineering and R&D processes and accelerate towards a more intelligent industry.

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Capgemini announces ‘augmented engineering’ offerings powered by Gen AI

Capgemini announces ‘augmented engineering’ offerings powered by Gen AI

The Group is extending its generative AI portfolio of services with new offerings tailored for engineering and R&D. The new services will help organizations unlock the value of Gen AI to accelerate R&D and augment engineering at all stages of the product development lifecycle

Oct 24, 2024

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205 KB pdf

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Paris, October 24, 2024 –
Capgemini
is extending its
Gen AI portfolio of services
with the launch of engineering and R&D-specific Generative AI (Gen AI) infused solutions for clients to accelerate innovation, streamline engineering and R&D processes with high-level automation, and the ability to unlock new discoveries. As a world leader in engineering and R&D services with deep industry knowledge, and a leading player in the AI market, Capgemini is well positioned to help organizations transform their engineering and R&D processes and accelerate towards a more intelligent industry.

With “
augmented engineering
”, Gen AI takes data-driven engineering and R&D to the next level.
The adoption of
a hybrid AI approach, combining Gen AI and AI with other kinds of engineering and scientific models, enables the delivery of outcomes with the precision, quality, regulatory compliance, and correctness required in engineering and science across industries. Engineering requires the ability to capture detailed data in many forms. For example, there is a vast difference in engineering application between a photo-realistic video and the schematic diagrams of an airliner avionics system, even if both are represented graphically.

Designed to help clients reap immediate benefits from Gen AI, augment engineering processes with AI, and accelerate the creation of new smart products and services, the first set of Capgemini’s
Gen AI offerings for engineering
and R&D includes:

“Augmented R&D Discovery”
: to accelerate scientific discovery, streamline R&D processes, identify novel scientific approaches, and generate new formulations. It augments research teams to reduce lead time for R&D discovery with data and AI-driven research hubs, reasoning engines, and digital R&D backbones needed to automate and orchestrate R&D processes, accelerate innovation – and unlock new discoveries in formulation-based industries. Example of applications include new drugs, aircraft fuel composition, tyre properties, components substitution in food, beverage and cosmetics.

“Augmented Software Product Engineering”
: an agent-based asset framework and associated consulting and engineering services to provide a uniquely holistic approach to improving product creativity and quality, development efficiency, and developer experience. Includes software lifecycle accelerators addressing product requirements optimization, code creation, product generation, and code migration.

“Augmented Product Support & Services”:
a Gen AI-enabled assistant to streamline software product support – making life easier for both support engineers and their customers in different industries e.g. telecommunications, industrial IoT or MedTech. Gen AI significantly reduces and automates product support work such as self-service deflection, guided remediation, while also removing linguistic barriers. It enables organizations to improve digital experience.

“Augmented Product Technical Publications”
: technical publications are regulatory-required documents providing all necessary information for the effective operation, installation, maintenance, and servicing of a manufactured product and its components. Capgemini has designed a technical publications factory model, custom-built production workflow assistant to reduce data retrieval time from hours to minutes, and to shorten publication authoring time from weeks to days.

“
Gen AI has the potential to
turn innovative technology into engineering value, with
products and services reaching new levels of intelligence and effectiveness. Our set of new ‘Augmented Engineering’ solutions are designed to take engineering and R&D to their next level and help clients to accelerate towards more intelligent products and services,
”

comments Franck Greverie, Chief Technology Officer, Chief Portfolio Officer and Group Executive Board Member at Capgemini. “
We are proud to be the preferred partner of industry leaders to support their ongoing transformation of
engineering and R&D processes and help them drive innovation and breakthrough discoveries. Given the demanding context of engineering that requires precision, regulatory compliance and risk tolerance, we are developing tailored solutions, augmented with Gen AI, to empower researchers, streamline processes and unlock substantial creativity and high-quality outcomes.”

Recognized as a Leader in AI and engineering

Capgemini was named a
Leader in The Forrester Wave™: AI services, Q2 2024
, among nine vendors evaluated on 19 criteria, grouped by current offering, strategy, and market presence. It was also recognized as a Leader in
2024 Zinnov Zones Ratings
for its overall Engineering, Research and Development and Digital Engineering Services.

The Group announced in July 2023 an investment plan of €2 billion over 3 years to strengthen its leadership in AI and has already trained over 120K team members on generative AI tools, thanks to its Gen AI Campus. It has established a dedicated generative AI practice to rapidly scale its capability, solutioning and delivery, as well as a
Generative AI Lab
to follow the evolution of the technology and research the most relevant use cases and collaborations with businesses or academia for clients, and a dedicated platform,
RAISE (Reliable AI Solution Engineering)
,

to industrialize its custom Gen AI projects.

Capgemini is also investing in its portfolio, to customize the uses cases and offers by industry, to build next-generation AI solutions for enterprises, and to generate more value for its clients, and in its partnerships, such as with
Google Cloud
,
Microsoft
,
Salesforce
,
AWS
,
Mistral AI
, and
Liquid AI
.

[1]
Capgemini’s approach, ‘
Augmented Engineering’
, powered by Gen AI in combination with AI and other types of engineering and scientific models, is defined to manage the demanding context of engineering, that requires precision, regulatory compliance and risk tolerance
.

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</reference>

<statements>
1. The common output pattern is platformization: Augmented Engineering and RAISE at Capgemini.
2. Talent scaling is equally prominent: Capgemini training of more than 120,000 people.
3. Client-facing examples include Capgemini engineering offerings.
4. As of 2026-09-13, the evidence also contains 2026 items, including IBM/Red Hat's May 2026 Project Lightwell, EY's July 2026 NVIDIA item, and Capgemini's May 2026 investment in the OpenAI Deployment Company, but it does not provide completion metrics for the 2023 commitments.
5. Capgemini's Augmented Engineering portfolio includes Augmented R&D Discovery, Augmented Software Product Engineering, Augmented Product Support & Services, and Augmented Product Technical Publications
6. The technical publications offering is described as a factory model and workflow assistant designed to reduce data retrieval time from hours to minutes and publication authoring time from weeks to days
7. Capgemini also uses RAISE, Reliable AI Solution Engineering, to industrialize custom GenAI projects
8. Client-level evidence is thinner than platform evidence, and the named cases in this section rest mainly on vendor announcements rather than audited outcome reports
9. Capgemini client or use case: engineering and R&D clients
10. Capgemini application scenario: R&D discovery, software product engineering, product support, technical publications
11. Capgemini evidence status: offerings described as designed solutions
12. Capgemini's 2024 release adds Salesforce, AWS, Mistral AI, and Liquid AI, and its 2026 related news describes an investment in the OpenAI Deployment Company
13. Capgemini says its engineering approach must manage precision, regulatory compliance, and risk tolerance
14. Capgemini says it has trained more than 120,000 team members on generative-AI tools through its Gen AI Campus
15. The evidence establishes application scenarios in engineering and R&D at Capgemini
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.