Perplexity is advancing Computer into enterprise analytics with a new data science-focused release that integrates the agentic workspace with live company data in Snowflake and Databricks. This development transforms Computer into a data agent for teams requiring SQL-backed answers, dashboards, analysis, and automations without the need to route every request through a data science queue.
The new capability allows users to ask questions over authorized warehouse and lakehouse data, with Computer generating queries, reading source tables, applying filters, and returning metrics tied to the underlying data. It is designed for business, product, sales, finance, and operations teams that need insights from internal data but may not be proficient in writing SQL themselves. Perplexity is positioning this as a tool for non-technical teams to conduct pipeline analysis, product usage reviews, customer segmentation, revenue trend summaries, and other recurring analytical workflows directly from Computer.
Computer now connects to Snowflake.
— Perplexity (@perplexity_ai) May 14, 2026
Run end-to-end work against live warehouse data and get answers with SQL, source tables, filters, and metrics.
It’s like a personal data science team, on call with accurate answers from live company data. pic.twitter.com/L1uQC6u5zZ
The feature is accessible through Perplexity’s Snowflake and Databricks connectors for Pro, Max, Enterprise Pro, and Enterprise Max users, with organization-level controls managed by admins. Snowflake support includes databases, schemas, tables, views, materialized views, and structured data such as CSV, JSON, and Parquet-backed tables. Databricks support encompasses Unity Catalog tables and views, Delta Lake tables, schemas, catalogs, external tables registered in Unity Catalog, and structured data. Unstructured data such as images, audio, video, and files stored in warehouse-specific storage areas is not supported at this stage.
The core technical component is Perplexity’s Data Map, a shared organizational semantic layer that Computer constructs from warehouse structure, table relationships, historical query patterns, and admin-provided business context. This enhances the agent's understanding of table meanings, metric definitions, and trusted query patterns. Admins can review and edit this map, refresh it, and approve proposed updates based on user feedback, maintaining a human review layer around shared data logic.
Perplexity is also introducing a robust governance aspect. Snowflake can be connected through user OAuth, service accounts with key-pair authentication, or programmatic access tokens, while Databricks uses individual OAuth identity. In both scenarios, queries run under existing platform permissions, so access is controlled by Snowflake RBAC or Databricks Unity Catalog rather than solely by Perplexity’s UI. Admins can also disable connectors, manage access, and enforce read-only behavior at the data platform level.
