Chariot

Chariot is a comprehensive MLOps platform designed to streamline the lifecycle management of machine learning models. It empowers data practitioners to develop, deploy, share, monitor, and remediate models efficiently, whether starting from scratch or working with existing models. The platform offers a no-code interface, allowing multidisciplinary teams to collaborate seamlessly and create data-driven outcomes.

Key features of Chariot include its robust role-based access control (RBAC) measures, which ensure secure data and project management for both federated teams and dataset restrictions. The platform is built with an open architecture eventing system and microservices, utilizing open APIs and open-source standards for datastores and models. This design enables multiple integration levels, including platform-level integrations with intelligence and command and control programs, service-level integrations for enhanced MLOps capabilities, and data or model imports.

Chariot provides full-spectrum auditability through its patent-pending data lineage, ensuring explainability and reproducibility of models as they move into production. The platform supports deployment across enterprise and edge environments, allowing users to connect various data sources, analytics, and visualization platforms through its API gateway. This facilitates a plug-and-play experience for monitoring, auditing, and remediating mission-critical models. By leveraging Chariot, organizations can enhance situational awareness, implement predictive maintenance, identify critical safety failures, track cybersecurity threats, and optimize business processes.