Monitaur

Founded 2019

Govern, validate, and monitor machine learning models across enterprise compliance lifecycles

Pricing model

Demo

You can use Monitaur to manage compliance, validate models, and monitor risk across enterprise machine learning projects. The system tracks model bias, drift, and performance while creating transparent audit trails for regulatory compliance. Teams can establish internal policies, assess vendor risk, and conduct model stress testing before deployment. By cataloging internal and third-party models in a single registry, organizations maintain visibility over their algorithms. It assists businesses in highly regulated sectors like insurance and banking to document model decisions, automate testing workflows, and satisfy rigorous reporting requirements.

What Monitaur does

Track model performance drift over timeGenerate compliance reports for regulatorsAssess risk on third-party vendor modelsStress test machine learning models before releaseDocument algorithm inputs and decision logsDefine enterprise-wide AI usage policiesConduct bias and fairness audits on training dataContinuous model bias and drift monitoringAutomated model validation protocols and testingThird-party vendor AI risk assessment and inventory trackingCentralized AI policy management and control mappingModel transaction evidence logging for audit complianceStress testing frameworks for complex models and agentsIntegration capabilities with MLOps and GRC systems