Xebia Highlights Critical Role of Data Foundation for AI Agent Success
Niels Zeilemaker, Global CTO at Xebia, emphasizes that a robust data foundation is essential for the successful deployment and scaling of AI agents within organizations. He notes that without proper data availability and cataloguing, AI agents may misinterpret information, leading to errors that are often attributed to the foundation rather than the agent itself. Xebia aims to assist organizations in transforming their AI strategies into production-ready solutions. The company offers specialized frameworks, including Agentic Data Foundation (ADF) and Xebia ACE: AI-Native Software Engineering, designed to prepare data for AI consumption, accelerate digital transformations, and optimize software development lifecycles.
A strong data foundation is crucial for the effective performance of AI agents, according to Niels Zeilemaker, Global CTO at Xebia. Zeilemaker states that if data is not properly prepared for AI consumption, even well-built agents can fail to find or correctly interpret necessary information, potentially joining unrelated data fields.
He highlights that such failures often stem from an inadequate data foundation rather than the agent's capabilities. Data cataloguing is identified as a critical area, as AI agents lack the human ability to seek clarification on poorly documented data, relying solely on available descriptions.
Xebia's objective is to help organizations transition their AI strategies into operational solutions that drive rapid transformation. The company prioritizes knowledge sharing and innovation, positioning itself as an authority in data and AI domains.
Among Xebia's offerings is the Agentic Data Foundation (ADF), which extends existing data platforms to host AI agents for both customer-facing and internal processes. This solution aims to accelerate the migration to modern data platforms, often involving co-development between consultants and clients.
Additionally, Xebia provides Xebia ACE: AI-Native Software Engineering, a framework designed to integrate AI across the entire software development lifecycle. This framework can accelerate delivery by up to 40% and reduce legacy transformation costs by as much as 70%, particularly benefiting larger enterprises with specific governance requirements.
According to AI News, Xebia presented these insights at events such as TechEx Global North America and AI & Big Data Expo.