Automatically register AI models from code workflows

AI systems are increasingly developed directly in engineering environments such as notebooks, Git repositories, and CI/CD pipelines, yet governance often begins only after models reach production. According to McKinsey’s 2025 Global AI Survey, more than 70% of organizations now use AI in at least one business function, accelerating the number of models, pipelines, and AI systems teams must track. However, AI assets are often documented manually and too late in the lifecycle. Capturing AI assets directly from development workflows helps organizations gain earlier visibility and establish governance from the start.

What’s new: Code-first AI registration

Code-first AI registration allows developers to register AI models and use cases directly from their development environment. Instead of manually documenting AI assets after deployment, models can be discovered and registered automatically during development workflows.

Through a CLI-based registration wizard, developers can scan their local project environment, identify AI models, and associate them with an AI use case. The registration process captures important metadata such as model name, framework version, source code location, and relationships between models and use cases.

This approach integrates governance directly into engineering workflows. Developers can confirm which model version should be associated with a base model and register it into the governance environment without leaving their development environment.

How code-first AI registration helps

AI development typically happens in environments that are disconnected from governance platforms. Data scientists experiment with models locally or in development pipelines, while governance documentation happens later.

This gap often results in missing metadata, incomplete documentation, or models that are deployed without being formally registered. Code-first AI registration bridges this gap by allowing developers to register AI assets directly during development workflows. Code-first AI registration solves for:

• AI models developed without governance registration

• Manual documentation of AI assets after deployment

• Missing metadata about models and development environments

• Limited traceability between development workflows and governance systems

• Difficulty linking model versions to AI use cases

How code-first AI registration works

Code-first AI registration introduces a command-line workflow that guides developers through the process of registering AI assets. The CLI scans the development environment and detects AI models present in the project repository. Developers can then select the relevant AI use case and confirm which model versions should be registered.

The registration wizard captures key metadata—including model name, framework version, source code location, and relationships between models and AI use cases—while seamlessly connecting this information to the broader Collibra Platform for unified governance, traceability, and visibility across your AI ecosystem.

Code-first AI registration delivers specific and essential value to key stakeholders across the AI lifecycle, from development to executive leadership:

• Data Scientists and ML Engineers: Register AI models directly from development workflows without switching tools improving efficiency and trust
• AI governance leaders: Ensure AI assets are registered early in the lifecycle, improving traceability and governance coverage
• Risk teams: Ensure earlier guardrails into AI systems before they reach production environments
• Chief Data and AI Officers: Establish governance foundations directly within AI development pipelines

Code first AI registry helps these personas:

• Development-time AI registration: Capture models during experimentation or development

• Automated governance onboarding: Ensure AI systems are registered before deployment

• Model lifecycle management: Track model versions and their relationships to AI use cases

Key takeaways about code first AI registry

Code-first AI registration integrates governance directly into AI development workflows. By allowing developers to register models directly from their development environment, organizations can capture governance metadata earlier and reduce the risk of untracked AI systems.

Join us for the upcoming Product Premiere to learn how:

AI models registered directly from development environments

• Automated capture of model metadata and relationships

• Earlier governance coverage in the AI lifecycle

• Improved traceability between development workflows and AI governance

Where to learn more about code-first AI registry

To learn more about code-first AI registration and the broader Collibra AI Governance capabilities, explore the following resources:

• AI Governance solution overview
• Collibra AI Governance product page

• 

  Shikhar Vaish

  Shikhar Vaish

  Senior Product Manager

  Collibra

• 

  David Talaga

  David Talaga

  Product Marketing Director

  Collibra

• 

  Pankuj Chachra

  Pankuj Chachra

  Senior Director of Engineering

  Collibra