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Get the data-powered advantage

Becoming a data-powered organization requires a strong data foundation – one that unites the enterprise and unlocks timely, accurate, and relevant insights – to drive real outcomes.

In the digital world, data makes the difference between success and stagnation. Data-powered organizations are 22% more profitable, and have twice the market capitalization rate, as their data-lagging counterparts. But becoming a data-powered organization is an enterprise-wide challenge that must be embraced by all parts of the business.

Capgemini helps organizations build their data foundation, enhancing, expanding, and advancing their existing data capabilities with powerful accelerators, frameworks, methodologies, and best practices gathered from decades of experience by our market-leading Insights & Data team.

Becoming a data-powered organization requires imagination. Our team of data engineers helps your organization envision and execute the data foundation that will help your business get the future you want.

    Custom Generative AI for Enterprise

    Prepare to be surprised by the collective power of human intelligence and our Custom Generative AI for Enterprise offer.

    IDEA by Capgemini

    The key to your data-powered organization.

      What we do

      Embrace the potential of artificial intelligence (AI) by transforming the way you are doing business, engaging with your clients and employees, and building a better society.

      Our data and AI strategy helps companies address the most critical requirements to fully utilize data, analytics, and AI for competitive advantage, market impact, and business results.

      Our offer focuses on four key areas to help clients craft a comprehensive, multifaceted data strategy, establish a scalable and sustainable data foundation, and ensure that their data, analytics, and AI fabric is agile, durable, and secure:

      1. Data and AI mobilization
      2. Data-powered innovation
      3. AI and analytics scaling
      4. Data and AI academy

      There’s no intelligence without data, at scale. These foundation services create modern data and AI platforms to deliver trusted AI solutions in production and at scale.

      Master Data Management (MDM)

      Our Master Data Management services provide the frameworks, accelerators and solutions you need to create a centralized information hub that avoids typical point-to-point integration of different applications. 

      MDM is a cloud-based solution powered by machine learning and AI. We help you harmonize the scattered and inconsistent master data gathered from all your internal data assets into a ‘single version of the truth – bringing a clear, consistent understanding of the data across your entire organization. 

      Data Estate & BI Modernization

      With the support of people, processes, and technology, our Data Estate and BI Modernization approach helps organizations transform their relationship with data.

      In a world where continuous, rapid change is the norm, where hybrid multi-cloud context is mainstream, we create with you an industrialized and secure data estate, and the data fabric, that supports the level of business innovation you need to remain a market leader.

      Industrialized Data & AI Engineering Acceleration (IDEA)

      Industrialized Data & AI Engineering Acceleration (IDEA) from Capgemini helps organizations turn their data sprawl into a valuable strategic asset.

      It’s time to rethink AI and analytics: from proof of concept to source of value. A functional asset to foundational capability. An experiment to an enabler.

      The true value of AI and Analytics cannot be realized from individual proofs of concept, but their at-scale deployment across business functions, units, and geographies.

      As an end-to-end transformation partner, we work with clients to develop the methodology, framework, and environment to enable large-scale, production-grade intervention and deploy AI and Analytics at scale.

      Our robust service offering and underlying business transformation capabilities address every aspect of the AI agenda – from laying a strong data foundation, to selecting the right tools, technology platforms, and agile practices, to establishing balanced operating models and ethical AI algorithms, to cultivating rich talent and partner pools.

      890 by Capgemini

      Data holds infinite possibilities – now is the time to activate its full potential. 890 by Capgemini is available on any cloud, and with a single interface, it puts you at the helm of your data. Data-powered decisions, delivered with confidence.

      The key is finding the data that’s right for you, easily and quickly. By combining an extensive ecosystem of industry-specific, open, and exclusive sources with your own data, we can help you create specific insights that allow you to make key decisions with confidence. Trusted, robust, and curated to your needs, 890 by Capgemini helps clients take their business forward with confidence.

      Machine Learning Operations (MLOps)
      Leverage MLOps to improve quality and robustness, shorten deployment times, and unlock the benefit of sustainable and scalable AI models.

      Organizations need strong support for scaling and industrializing AI/ML models. Capgemini provides a proven framework to stabilize, standardize, and optimize the entire AI/ML journey across popular cloud services, as well as on-premises setups.

      Our MLOps framework, built on the key principles of DataOps and DevOps, offers clients access to reusable templates and pipelines to enable a model ecosystem, a mix of cloud native services and third party/open-source stack for added flexibility, customized model approval workflows for enhanced governance, and extensive plugins to enhance model monitoring.

      Federated learning
      Federated learning provides organizations with a decentralized model training capability. With our cutting-edge approach, models are trained locally and securely, aggregated centrally, and deployed back on edge – all without moving data outside its boundary.

      AI and ML-driven business decisioning provides enormous value to the organization. However, challenges around data security and privacy, as well as the scalability of the platform, are major obstacles to widespread AI/ML adoption.

      Federated learning, along with EDGE AI enablement, helps organizations overcome these challenges. Capgemini’s state-of-the-art Simulation Lab for Federated Learning & Edge Intelligence allows customers to leverage best-in-class FL frameworks to validate thinking and identify optimal use cases as they begin or continue their FL journey.

      Intelligent process automation leverages a unique and differentiating approach that encompasses an end-to-end perspective from ideation to production.

      This enables you to seek guidance on starting an automation journey, scale up operations, enjoy sustainable automation benefits, and pursue capability growth and innovation that benefits from our world-class capability, and vertical and horizontal process experience.

      Client stories

      Expert perspectives

      Meet our experts

      Eric Reich

      AI & Data Engineering Offer Leader and Global Head, Insights & Data
      Eric has over 20 years of experience and is been part of Capgemini Group portfolio team for Insights and Data, global practice. He is currently leading AI & Data Engineering team globally. With 16+ years of experience in the FS sector and 10+ years in the cloud and data space , he had the opportunity to work with some of Fortune 500 customers in the Assessment , Design and Execution phases of their data driven transformation.

      Dinand Tinholt

      Vice President, Insights & Data, Capgemini
      “Even while investment levels in data and AI initiatives are increasing, organizations continue to struggle to become data-powered. Many have yet to forge a supportive culture and a large number are not managing data as a business asset. For many firms, people and process challenges are the biggest barriers in activating data across the enterprise.”

      Mark Oost

      Global Offer Leader, AI Analytics & Data Science
      Prior to joining Capgemini, Mark was the CTO of AI and Analytics at Sogeti Global, where he developed the AI portfolio and strategy. Before that, he worked as a Practice Lead for Data Science and AI at Sogeti Netherlands, where he started the Data Science team, and as a Lead Data Scientist at Teradata and Experian. Throughout his career, Mark has had the opportunity to work with clients from various markets around the world and has used AI, deep learning, and machine learning technologies to solve complex problems.

      Sebastien Guibert

      Vice President, Intelligent Process Automation, Offer Leader
      A Data and AI Leader, serves as the Global Portfolio Head for Business Services and Group Offer Leader for Intelligent Business Process Operation and Intelligent Process Automation. With over 24 years of experience, he excels in managing AI portfolios across various sectors, optimizing enterprise processes, and deploying advanced Data technologies for scalable AI insights. Sebastien’s qualifications include BAC +5 in IT Management and BAC +2 in Mechanical Engineering, along with PMI certification since 2009.

      Steve Jones

      Expert in Big Data and Analytics
      Steve is the founder of Capgemini’s businesses in Cloud, SaaS, and Big Data, a published author in journals such as the Financial Times and IEEE Software. He is also the original creator of the first unified architecture for Big Fast Managed data, the Business Data Lake. He works with clients on delivering large-scale data solutions and the secure adoption of AI, he is the Capgemini lead for Collaborate Data Ecosystems and Trusted AI.

      Gianfranco Cecconi

      Collaborative data ecosystems lead, Capgemini Invent
      “The EU’s Data Governance Act has renewed the drive for governmental initiatives aiming to empower citizens, businesses, and organizations through data. The EU data strategy is alive and meaningful to all of us in the different roles we play in our data ecosystems. The Member States’ open data programs are among the pillars that this transformation builds upon.”

      Aruna Pattam

      Head of AI Analytics & Data Science, Insights & Data, APAC
      Aruna is a seasoned data science leader with a successful track record of developing and implementing data and analytics and data science solutions through cutting-edge technologies, agile development, continuous delivery, and DevOps. With over 22 years of experience, Aruna is a Microsoft-certified data scientist and AI engineer. She is a member of the Responsible AI Think Tank at CSIRO NAIC, which focuses on the responsible and ethical use of #AI in businesses in Australia, and a known public voice in Australia for Women in AI.

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