What is an Asset Schema?

An Asset Schema defines the structure and fields for every AI system in your inventory. It is essentially the template that determines what information gets captured for each Asset. Think of it as the blueprint that keeps your entire AI inventory consistent and organized.

Every organization describes AI differently. A bank might need to track regulatory jurisdiction and risk tier. A healthcare company might need to capture patient data involvement. A tech company might care most about model architecture and deployment environment.

Without a consistent structure, teams end up describing AI systems in their own way. One team tracks the model owner, another does not. One team classifies risk, another skips it. That inconsistency makes it impossible to get a reliable view across your organization or run standardized governance processes.

Our Asset Schema solves this. It creates a single, agreed upon structure that every AI system in your inventory follows. When every Asset uses the same schema, your data is clean, comparable, and ready for governance at scale.

What is inside a schema

In our platform, an Asset Schema is made up of fields organized into sections. We provide a set of base fields that every organization needs out of the box, and you can add custom sections and fields that match your specific requirements.

Base fields we include:

• Name and description of the AI system
• Owner and responsible business unit
• Current status and lifecycle stage
• Risk classification level
• Source and discovery information

Custom sections you can add:

• Regulatory and compliance classifications specific to your industry
• Data sensitivity and privacy indicators
• Business purpose and use case categories
• Deployment environment details
• Vendor and third party information
• Internal review and approval tracking fields

You choose what matters to your organization. We give you the foundation, you make it yours.

How schemas work in our platform

1. Your governance team defines the schema using our configuration interface - selecting which fields and sections are needed

2. You can save it as a Draft while your team reviews and iterates on the structure

3. Once your team is happy with it, you Publish the schema, making it the active template for your inventory

4. Every Asset created from that point forward follows this structure, keeping your entire inventory consistent

5. You can update the schema anytime as your governance needs evolve - existing data is preserved

Asset Schemas vs Artifact Schemas

We support two types of schemas. They work together to keep everything in your inventory structured from top to bottom.

Asset Schema - Defines the structure for your AI systems. This is what your governance team works with most, since all assessments, workflows, and compliance actions happen at the Asset level

Artifact Schema - Defines the structure for the individual evidence items we discover during scanning. This keeps your raw discovery data consistently categorized and traceable

What this means for your team

A well defined schema makes everything in the platform work better:

• Consistency - Every AI system is described the same way, so you can compare, filter, and report across your whole portfolio
• Completeness - Required fields make sure critical governance information is always captured - no gaps, no missing data
• Compliance readiness - When regulators ask about your AI systems, you can answer immediately because every Asset has the same structured information
• Scale - As your AI portfolio grows from 10 systems to 500, your inventory stays manageable because everything follows the same template
• Automation - Standardized fields let us trigger workflows, route reviews, and generate reports automatically based on your schema data