Embrace Auditable AI now. Avoid compliance risks later.
Organizations use Verta to ensure that their AI systems and processes are transparent and accountable, helping them to comply with AI laws and regulations
Legal and regulatory risks make Auditable AI a “must-have”
Auditable AI is a complement to Responsible AI, ensuring that an organization can fully document its ML models across their end-to-end lifecycle.
The goal of auditable AI is to demonstrate that the organization developed, deployed and managed a model in accordance with legal requirements and Responsible AI principles. Auditable AI has become essential for organizations to meet legal challenges and audit requirements embodied in AI regulations.
The foundations of successful Auditable AI
Auditable AI is about creating an accessible, clear audit trail for ML models and AI systems and processes.
Successful Auditable AI requires that the company have a well-established governance framework, including robust ModelOps capabilities for documenting and monitoring models, as well as tracking and reporting on input data and data sources, algorithms used, outputs and decisions made, performance metrics and user and system logs.
Verta helps companies meet the requirements of Auditable AI
- Record release lifecycles from development through archive.
- Standardize model documentation, model schema and API management.
- Publish all model metadata, documentation, and artifacts in a central catalog.
- Review training data for bias, and manage inputs/outputs of the modeling process.
- Obtain full reproducibility using configuration, code, data and environment variables.
- Track input, output and intermediate results, and access detailed audit logs.