Hi all! Pete, Co-Founder of Liquibase here.
Today we announced new AI governance capabilities in Liquibase Secure and a strategic partnership with MongoDB that extends enterprise control to the database layer.
The challenge:
AI governance stops at the model, but risk lives in the database. As enterprises move faster with AI, most governance frameworks focus on model bias, explainability, and privacy. The greater risk often hides at the data layer. AI agents that can write or modify database queries can alter or delete production data, introduce schema drift, or corrupt AI training sets before traditional security controls ever detect them.
According to the 2025 State of Database DevOps Report, 78% of organizations struggle with AI-driven data challenges, while Gartner estimates that 40% of agentic AI projects will be canceled by 2027 if they lack clear governance at the data layer.
The solution:
Liquibase Secure provides database-layer controls for AI workloads:
● Automated Policy Enforcement: Blocks destructive AI-generated changes before production across 60+ database platforms
● Role-Based Approval Enforcement: Integrates with enterprise CI/CD and access controls to ensure all database changes, including those generated by AI, are reviewed and approved prior to deployment
● Automated Drift Detection: Identifies unauthorized schema modifications and environment inconsistencies before they affect downstream systems or model training
● Tamper-Evident Audit Trails: Creates a verifiable record of every change for frameworks such as SOX, HIPAA, GDPR, NIST AI RMF, and the EU AI Act
● Targeted Rollback: Reverses problematic changes in minutes instead of hours
● Schema-Level Data Lineage: Captures the full history of structural evolution, which is critical for AI model provenance and regulatory audits
MongoDB Partnership:
Liquibase also announced a new strategic partnership and technology integration with MongoDB, the unified data platform that powers modern, data-intensive, and AI-driven applications.
MongoDB’s flexible document model is a powerful enabler for rapid iteration and experimentation in dynamic AI environments. As agility drives growth, managing and tracking evolving schemas across many projects becomes a critical governance need. Issues like inconsistent field names or untracked schema drift can quietly disrupt analytics pipelines, corrupt training data, or derail audits over time.
Liquibase Secure integrates directly with MongoDB to provide continuous governance without slowing innovation. Every collection change runs through automated policy checks. Drift detection flags unapproved updates before they spread. Structured, tamper-evident logs deliver a single source of truth for auditors and data scientists.
Learn more:
Read the blog
Download the white paper
Register for the webinar (Dec 10th, 12pm ET)
As always, we’re here to answer questions about the MongoDB integration, AI governance capabilities, or how this fits with your current workflows.