Pylar AI

Pylar AI is a security data access governance platform for AI agents. Its core purpose is to mitigate the risk of securely connecting AI agents to production data stacks. By leveraging controlled data views and MCP tools, it provides AI applications with unified, governed data access while ensuring safety and compliance.

The platform guarantees security through the core abstraction layer of 'data views'. Administrators predefine the data scope AI agents can access (e.g., specific SQL views). Agents can only access data through these views and cannot directly connect to the underlying databases, achieving fine-grained data access control and row-level security.

Pylar AI supports connecting to a variety of mainstream data sources, including BigQuery, PostgreSQL, Snowflake, and more, as well as SaaS tools like HubSpot, Stripe, Zendesk, and can perform cross-source joins and data merges.

Primarily aimed at data scientists, AI engineers, and data platform teams. Users should have a basic understanding of data querying (e.g., SQL) and AI agent development concepts, but the platform lowers the technical barrier with AI-assisted automation.

The MCP tool is a set of function modules built on data views that AI agents can call directly. When creating, users can, on top of predefined data views, use the platform interface (AI-assisted or manual configuration) to define the tool's name, description, and query logic, without writing backend API code.

The platform provides a unified control panel to centrally monitor all AI deployments. Features include tracking tool call success and error rates, analyzing query performance and patterns, viewing raw logs, and a built-in evaluation framework to continuously diagnose and optimize data access quality and security.