The solution makes it possible for proprietary AI agents with advanced human data engineering teams to assess, migrate, monitor, and operate enterprise data platforms

India, July 14 : Xebia, a global AI-first, digital transformation, and engineering leader, announced Xebia Axis: Agentic Data Foundation, a solution that gets enterprise data ready for AI with the speed of automation and the discipline of governed engineering. It combines proprietary AI agents with human data engineering teams to assess, migrate, monitor, and operate enterprise data platforms, completing migrations roughly three times faster than conventional, human-led delivery without trading away governance or data quality.

The solution addresses a change in how enterprise data is consumed. Data platforms were designed for people who can work around inconsistencies. Autonomous AI agents act on data as they find it. Xebia Axis makes the data, governance, and controls that those agents rely on consistent, auditable, and production ready. Human teams set strategy and govern quality, while agents execute with roughly 10 times the leverage of a purely human-led team.

At a Glance

• What it is: An agentic data foundation that assesses, builds, migrates, monitors, and operates enterprise data platforms within a single solution.

• How it works: Human teams set strategy and govern quality. Proprietary AI agents perform assessment, migration, monitoring, and remediation tasks.

• Six modules: Readiness, Platform, Knowledge, Migration, Observability, and Operations.

• Timeline: Xebia Axis for Readiness produces a data readiness score and migration blueprint in two to four weeks. Traditionally, build and migration can run for several months.

• Governance: Access control, audit logging, data residency, and bias controls are part of the platform rather than added afterwards.

• Interoperability: Works across major cloud platforms and large language models; no single-vendor requirement.

“Enterprises have spent years moving data to the cloud, but many still cannot put AI into production because the underlying data and governance are not ready,” said Anand Sahay, Chief Executive Officer, Xebia. “Xebia Axis closes that gap, so our clients can move AI into production faster than competitors still wrestling with legacy data platforms.”

How Xebia Axis Works

Xebia Axis covers the full data lifecycle in one solution rather than the separate tools enterprises typically assemble for each stage. Six modules run from initial assessment through ongoing operations: Readiness maps the data estate and produces a prioritized migration blueprint; Platform generates governed, policy-validated infrastructure as code; Knowledge converts content held in documents, email, and disconnected systems into a governed data layer for AI; Migration automates data and pipeline conversion with parity checks before cutover; Observability monitors data quality, service levels, and agent activity; and Operations performs root-cause analysis after go-live and submits fixes as pull requests for human review.

Agents operate within controls for access, audit logging, and data residency, and data remains within the client’s environment. Xebia Axis works across major cloud platforms, including AWS Redshift, Google BigQuery, Databricks, Snowflake, and Microsoft Fabric, and major large language models, including Claude, OpenAI, Gemini, and Mistral AI.

“The same agent technology that makes data debt urgent also makes it faster to resolve,” said Niels Zeilemaker, Xebia’s Global CTO Data & AI. “Xebia Axis puts purpose-built agents alongside senior engineers to build and run data platforms in production, with governance built into the platform itself.”

Built on Partner Platforms

Xebia Axis is built to run on the platforms enterprises already rely on. As a partner of Amazon Web Services, Microsoft, Google Cloud, Databricks, and Snowflake, Xebia deploys it natively on each. It provisions governed environments, migrates workloads, and operates pipelines within the customer’s chosen stack. Because the solution is platform- and model-agnostic, organizations can integrate these clouds and data platforms with their preferred large language models and adapt as their architecture evolves.

Early Engagements

• Early Xebia Axis: Agentic Data Foundation engagements span banking, travel, and retail, where the value at stake is well documented:

• A global bank used the solution to consolidate fraud and credit data from separate batch systems into one governed platform with real-time access for its detection models. Cloud data-platform modernizations for banks of this size and medium complexity typically reduce infrastructure costs by 30 to 50 percent within the first two years.'

• A global airline applied Xebia Axis to modernize fragmented operational and customer data. By automating estate discovery, code conversion, and validation, Axis completes migrations roughly three times faster than conventional means. It brings traditional migrations, which usually last 12 to 18 months, down to a few months.

• A global retailer used the solution to consolidate duplicate pipelines into a single, governed, continuously monitored platform to address data-quality failures. The retailer has benefited from more consistent, trustworthy data across its reporting and operations, with issues caught and resolved before they reach downstream systems.

Availability

Xebia Axis is available globally today. Organizations can begin with Xebia Axis for Readiness as a standalone assessment, which produces a data readiness score, estate inventory, and migration roadmap in two to three weeks; assessment fees are credited toward a subsequent migration. More information is available at: www.Xebia.AI/Axis

Recently, Xebia launched Xebia Ace, an AI-Native Engineering solution. It is an AI-Native software engineering framework designed for pragmatic, outcome-driven modernization and digital transformation, which embeds AI across the entire SDLC to accelerate delivery by up to 40%.