Astralis Overview: AI Native DSPM

What this video covers

Astralis delivers AI-native Data Security Posture Management (DSPM): discovering data assets across the enterprise, classifying and labeling them with the Fides governance ontology, and identifying sensitive data and regulatory risk. Coverage spans warehouses, databases, third-party SaaS vendors, cloud providers, single sign-on platforms, websites, and mobile applications. Classification and risk evaluation are driven by the Astralis Large Language Risk & Regulatory Model (LLRM).

This video walks through:

• Continuous detection and discovery across the enterprise surface, including warehouses, databases, SaaS, cloud, SSO, web, and mobile
• Fine-grained, field-level classification and labeling of data such as location, demographic, contact, and behavioral data and IP addresses, with confidence scores and an explanation for each label
• Proactive risk identification, including consent-ignored violations and compliance gaps
• Vendor and system descriptions with assigned processing purposes, owners, and stewards
• Continuous data inventory and risk register updates, with export to regulatory templates such as an Article 30 data map

How it works

Astralis monitors assets across the enterprise surface and flags those that need attention, including risks such as an asset collecting data where consent was ignored. For data stores like a BigQuery warehouse, it labels each field with a precise data type, shows its confidence, and explains how it reached the label. You approve assets to add them to the data inventory, where Astralis maintains them and surfaces them into the risk register. From there the inventory exports into regulatory reporting templates, including an Article 30 data map grouped by processing purpose.