Axis for Data Products: From Data Contract to Certified Marketplace

Data products are the foundation of modern data strategy. But building them has always been slow, manual, and with misalignments being the soup du jour. The business defines what they need. Engineering interprets, builds, and delivers. By the time the product reaches the business, well, the original intent is often lost in translation.  

We are ready to change this. Xebia Axis for Certified Data Products creates a standardized pipeline that turns a business requirement into a certified, marketplace-ready data product: full governance, documentation, and quality enforcement built in from the start. 

The gap isn't ambition, it's execution. According to Xebia's Data & AI Monitor 2026, only a minority of organizations believe they are fully harvesting the value AI brings, even though most know exactly where to apply it. Data products are the bridge between that intent and that value. 

In this blog, we'll unpack how Axis reimagines data product creation, walk through what the process looks like step by step, and explain why the traditional "build and hope" approach no longer works. 

Certified Data Product: Discover, Trust and Use 

Xebia Axis for Certified Data Products sets out to completely rewrite the creation of data products. It standardizes the entire lifecycle and outputs a certified data product that a business can discover, trust, and use. 

The process does not start from the code, but with a data contract, the single source of truth that ensures the business and engineering teams are aligned on what "correct" means. Xebia Axis agents then build, certify, and list the product in a marketplace, all with governance built in. Naturally, human teams will set the strategy, review the output, and approve before release. 

The Data Product Gap 

In traditional organizations, data product creation follows a broken pattern: 

This approach is slow and unreliable. On average, creating a single data product takes four to eight weeks in the traditional model. Teams manually code pipelines, test datasets, and iterate through multiple rounds of feedback. 

Data products need to be certified, discoverable, and governed. If they are not, then it is highly probable that agents won't trust them. 

Traditional vs. Axis Data Product Build 

In the traditional model, data products are built through a fragmented, manual chain. Engineers write code, create datasets, hand them over, and wait for feedback that inevitably leads to rework. There is no single specification. Quality is inconsistent. Products are invisible to consumers. 

Axis replaces this with a structured, automated approach: 

How Does the Axis Data Product Process Work? 

The Axis process for certified data products follows three distinct phases. 

Phase 1: The Data Contract 

The journey begins with a business user interacting with the agent through a straightforward chat interface. The business user explains their specific needs, for example, analyzing campaign leads from the last 30 days. The agent, trained on enterprise context, will ask follow-up clarifying questions, such as what variables are needed or what quality checks should be run. 

Through this conversation, the agent captures every full requirement in detail. The output is a data contract with four parts: 

1. Business Requirement – A plain English summary that the business user can read and sign off on. 

2. Chat History – The complete conversation between the agent and business user, captured for auditability. This is the immutable record of how the requirement was gathered. 

3. Technical Specification – The agent translates the requirement into technical details: data sources, schema mapping, quality rules, access classification, and data product definition. This follows the ODPS (Open Data Product Specification) and ODCS (Open Data Contract Standard) open frameworks. 

4. Version Control – Each contract has a version, enabling future enhancements and change tracking. 

Once everything has been verified and checked, the business user can sign off the data contract. This process eliminates all ambiguity and guesswork, leading the user through a clear and straightforward process. 

Phase 2: The Agent-Led Build 

Once the data contract has been approved, it is time for the Data Engineering Agent to take over. The process is agent-led but engineer-controlled: 

Note: The ontology is the shared semantic layer that connects concepts, like Customer, SKU, or Sales Order, across every certified data product, so agents and humans use the same definitions everywhere. 

Throughout this phase, the agent works under the engineer's supervision, so code is never generated and deployed blindly. It is constantly reviewed, tested, and validated, at every stage. This is the disciplined governance that makes Axis a complete different experience from unchecked automation. 

Phase 3: Business UAT and Marketplace Listing 

With the product built, it's time for the business to sign off before release. The business user sees a validation interface showing: 

If approved, the product goes to the marketplace.  

This is the central catalog where all certified data products are discoverable: 

If a user cannot locate the exact product they need, they can request a new data product through the marketplace, starting the process again. 

Why Do Certified Data Products Matter for the Agentic Enterprise? 

Organizations are investing heavily in AI. But they are pushing agentic AI into production on top of brittle pipelines and missing lineage, systems never designed for autonomy. Xebia’s Data & AI Monitor 2026 confirms that organizations know where to apply AI, but value realization remains stubbornly low. 

Data products are the bridge between strategy and execution. They provide: 

With Axis, these products are generated in a matter of weeks, not months. Human teams set strategy and govern quality, while agents execute with roughly 10 times the leverage of a purely human-led team. 

From Request to Certified Product 

Your data product creation was built for a world of slow, manual, and fragmented delivery. Agentic AI demands something better. It demands consistent, governed, discoverable data products that agents and humans can trust. 

Xebia Axis for Certified Data Products delivers a standardized pipeline from data contract to certified marketplace listing. It replaces manual guesswork with automated governance, invisible products with discoverable assets, and questionable quality with certification. 

The same agent technology that makes data debt urgent also makes it faster to resolve. Xebia Axis puts purpose-built agents alongside senior engineers to build and run data products in production, with governance built into the platform itself. 

Take the next step towards an Agentic Enterprise with data products that are certified, governed, and ready to trust. Are you ready to find out more about Xebia Axis for Certified Data Products?