Capgemini launches new generative AI services portfolio – Times of India

What the generative AI portfolio includes:
– The “Generative AI strategy” empowers CXOs to identify and prioritise the most pertinent generative AI use cases for their businesses. It allows them to showcase the tangible value that can be attained and establish the necessary groundwork in terms of people, processes, and technology to expand their generative AI investments while effectively managing potential risks.

– The implementation of Generative AI for Customer Experience revolutionises customer interactions through the deployment of four specialized generative AI assistants. It enables hyper-personalized customer experiences using a synthetic design assistant, improves customer self-service with personalized chatbots, enhances customer care services with a content and knowledge assistant, and optimizes sales teams’ performance with a product & offers knowledge assistant.
– The implementation of Generative AI in Software Engineering enhances efficiency and quality throughout the entire software life cycle, encompassing design, coding, documentation, testing, deployment, and operations. It expedites the time to market for new software and aids enterprises in reducing technical debt by facilitating extensive modernization efforts for legacy software. Additionally, it contributes to heightened security by automatically identifying bugs or vulnerabilities and suggesting appropriate adjustments to software development teams, thereby reducing the attack surface.
– The utilisation of Custom Generative AI for Enterprises empowers businesses dealing with sensitive data to deploy customized generative AI assistants specifically tailored to leverage their proprietary information, maximizing the impact on business value. The Group has developed a platform that combines the capabilities of pre-trained open large foundation models (LFMs) with enterprise proprietary data, allowing the fine-tuning of LFMs to suit the individual requirements of each client. By building customized models that draw from the company’s expertise, these AI solutions can generate unique and reliable outputs, facilitating progress on various fronts, such as enhancing customer experience, accelerating R&D efforts, and boosting performance in support and business functions.