Xebia launches agentic data platform to help enterprises prepare data for ai
Xebia has introduced Xebia Axis, an agentic data platform designed to help enterprises modernise, migrate and manage data environments for artificial intelligence (AI) deployments.
The platform combines proprietary AI agents with human data engineering teams to automate data assessment, migration, monitoring and operational tasks while retaining governance and quality controls. According to the company, the approach can reduce migration timelines to roughly one-third of those associated with conventional data migration projects.
The launch reflects a growing industry focus on preparing enterprise data for AI applications. While many organisations have moved workloads to the cloud, fragmented data environments, inconsistent governance and legacy systems continue to slow the deployment of AI models into production.
Xebia said the platform is designed to address these challenges by integrating six functions into a single solution covering data readiness assessment, platform provisioning, knowledge management, migration, observability and operations. Human teams remain responsible for strategy and governance, while AI agents automate engineering tasks including infrastructure provisioning, data conversion, monitoring and issue remediation.
According to the company, the platform incorporates governance capabilities such as access controls, audit logging, data residency and bias management, and keeps enterprise data within customer environments. It is compatible with multiple cloud platforms, including AWS Redshift, Google BigQuery, Databricks, Snowflake and Microsoft Fabric, as well as large language models (LLMs) from OpenAI, Anthropic, Google and Mistral AI.
Anand Sahay, Chief Executive Officer of Xebia, said many organisations have completed cloud migration projects but continue to face challenges in deploying AI because their data environments and governance frameworks are not sufficiently prepared for production-scale AI workloads.
The company said its Readiness module can generate a data readiness assessment and migration blueprint within two to four weeks, compared with conventional assessment and migration projects that often take several months.
Xebia also disclosed that the platform has been deployed in early engagements across the banking, airline and retail sectors. According to the company, these implementations have included consolidating fraud and credit data for a global bank, modernising operational and customer data for an airline, and streamlining duplicate data pipelines for a global retailer to improve data quality and governance.
Commenting on the launch, Niels Zeilemaker, Global Chief Technology Officer for Data and AI at Xebia, said the increasing adoption of AI has also heightened the need to modernise enterprise data estates. He said the platform combines AI agents with engineering teams to automate the development and operation of governed data platforms.