gravityAI

Founded 2019

Inventory, deploy, and govern models across your private cloud and enterprise systems

You can use gravityAI to track, build, and deploy machine learning models directly within your private cloud or on-premise infrastructure. It catalogs every internal model and third-party vendor service across your company, creating an automatic audit trail of ownership, risk levels, review sign-offs, and data sources. Teams can connect existing systems, assemble workflows using visual drag-and-drop tools or code, and test candidate versions against live examples before updating production. It automatically documents model behavior and lineage to satisfy strict regulatory compliance and internal security audits.

What gravityAI does

Catalog internal and third-party models across enterprise departmentsDeploy models into private cloud and on-premise infrastructureBuild data pipelines using visual drag-and-drop componentsRun side-by-side version evaluations against real sample datasetsExport comprehensive compliance and audit trails for regulatory examinersAssign ownership and access permissions to specific modelsConfigure automated cost caps and usage guardrailsAutomatic documentation of model risk levels, ownership, and data sourcesPrivate cloud, on-premise, and air-gapped environment supportVisual drag-and-drop workflow builder alongside code optionsComprehensive inventory tracking both internal and vendor-licensed AI modelsPre-production side-by-side comparison testing against real dataBuilt-in audit trails tracking approvals, reviewers, and active datesCatalog for discovering, sharing, and reusing approved models across teamsAutomated guardrails with default limits and cost controls