Verta Model Catalog
Manage Your AI‑ML Models in One Place
Verta Model Catalog is a central repository to manage and deploy production-ready models.
Verta Model Catalog ensures a reliable and automated release process.
One Unified Hub to Publish Release Ready Models
Select the best fit models from model experiments and stage them for release
Publish all the model metadata, documentation and artifacts in one central repository
Connect to experiment management system for end to end information tracking
Record state transitions and manage release lifecycle from development, staging, production to archived
Model Validation and CI/CD Automation
Integrate with existing CI/CD pipelines like Jenkins, GitOps et al
Use webhooks to trigger downstream actions for model validation and deployment
Automatically track model versions and tagged releases
Manage Model Governance and Compliance
Release models once they pass basic security and fairness checks
Configure and customize model promotion schemes and approval process
Build custom approval workflows and integrate with preferred ticketing system
Access detailed audit log for compliance
Increase Visibility and Collaboration
Unified view of all the models, documents, and artifacts for better monitoring and discoverability
Facilitate sharing, and collaboration of production-ready models
Setup granular access control editors, reviewers, and collaborators
Take a Tour
One platform, all of your model delivery needs.
Manage
Full-lifecycle model management from experiment tracking to production registry
Deploy
Ensure production-quality operations with reliable governance and auditing.
Operate
Reliable batch and real-time inference & serving on any k8s infrastructure.
Monitor
Keep models relevant with real-time decay monitoring and logging.
Compatibility
We Integrate With Your AI-ML Stack
Verta supports all of these popular platforms and frameworks—plus many, many more.
Don't take our word for it. See what others are saying.
Scribd utilizes machine learning to optimize search, make recommendations, and improve new features.
LeadCrunch's Data Science teams create Machine Learning models that help B2B companies find better prospects faster.
A leading collaboration platform utilizes ML to prevent abuse, make recommendations, and improve user experience.