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Along with Postgres as Data Warehouse, Probyto AIMS provides BI engineers 'integrated' opensource tools for best practices. From building dashboards with Superset to extracting data reports in Hue, all connected to a central place for ease of use, access and management.

If your password is stolen or guessed, without 2nd Factor Authentication, the password alone is useless. Probyto AIMS allows the admin to set 2FA on user accounts using Google Authenticator App, thus making access more secure.

We have recently integrated the best open source tools for Data engineering practices with Probyto AIMS. Users will be able to build and manage data connectors with Airbyte, apply transformations with Data Build Tool (DBT) and run/schedule jobs for transformations & building data pipelines with Airflow; all connected to a central place for ease of use, access and management.

Probyto AIMS allows you to restrict access to the platform by selecting countries. This makes sure your AIMS data is only accessible from pre-defined countries and hence comply data residency.

Each user can have different sets of roles and access privileges. Probyto AIMS provides an option to select roles based on your work and AI resource & Tools requirements.

Cyber-attacks have resulted in business-critical data being exposed in various companies. Probyto AIMS provides you the features to restrict access from trusted IPs only by assigning IPs while adding or editing users.

In an organization, different skills cost differently. In Probyto AIMS you can set the average cost per hour of each of your resources to keep track of the cost of building the AI Asset. Better cost management leads to cost optimization

Get access to the right stack for your MLOps team to manage code & run CI/CD pipelines with GitLab, deploy models with serverless architecture OpenFaaS, access model images with Docker Registry, manage APIs with Kong; all connected to a central place for ease of use, access and management.

Probyto AIMS comes with integrated tools for Machine Learning engineers & Data Scientists to start building and tracking models. We have integrated JupyterHub for building models using various kernels, Mlflow for tracking model experiments and Great Expectations to monitor data quality. The right ML stack for users all connected to a central place for ease of use, access and management.