Manage More Models in Production Faster, Easier, & For More Teams
What is Enterprise-Ready in an AI Platform?
Datatron has already been battle-tested by Fortune 1,000 Enterprise brands in production. Many AI/ML platforms exist, but once you ask the right questions, you soon learn that they do not have models in production on their platform. To deliver this, Datatron was designed with Enterprise requirements in mind, anticipating common approaches to infrastructure, technologies, security, and access control.
Flexible GUI and API Interface
Datatron’s API-based implementation provides incredible flexibility for teams that would like to leverage specific components of the platform and integrate these functionalities with their own customized tools. Flexibility is essential for enterprises to leverage existing infrastructure without having to disrupt existing processes.
The graphical user interface (GUI) provides an easy-to-use interface where most tasks are accomplished with a few clicks.
Support any cloud - On-prem, Public Cloud
Based on Kubernetes, the Datatron platform can be deployed to any Enterprise environment, including on-premises, Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure, and even Edge and air-gapped environments. This flexibility allows businesses to take advantage of AI on their own terms rather than on the terms of specific vendors.
Role-based Access Control
Enterprises have multiple business units with different security and authorization requirements. The HR team will have access to certain resources from the marketing team and vice versa. Within those same teams, you have technical users who will have different access levels compared to business users.
Datatron allows you to define these varying user access controls to ensure proper security and privacy are being adhered to.
Connectors with Popular Data Warehouse
Integration with existing data warehouses, including HDFS, Cassandra, Snowflake, AWS S3, Teradata, Azure Blob
In addition to your ability to define local users’ permission levels, Datatron can utilize existing LDAP and authentication to assign security permissions.
Datatron integrates with existing user groups defined in the Enterprise LDAP to provide differentiated access groups and users, reducing the need to configure access levels manually.
Why AI/ML DevOps & ML Engineers Love Datatron
- Models not performing in production the same as in the lab
- Models built on different tech stacks, languages, and libraries
- Supporting model health, explainability, & Governance requirements from Executives, Data Scientists, & multiple LOBs or BUs
With Datatron, AI/ML DevOps Engineers and ML Engineers have one simplified platform that is development stack agnostic. It has an easy-to-read Dashboard that tracks model bias, drift, anomalies, and performance. The Model Catalog and other Governance features make audits a breeze.