Pylar provides a secure middleware layer that connects AI agents to databases such as Postgres and Snowflake, letting teams define precise data access policies and build custom tools without writing API code. It offers observability across AI deployments and keeps compute costs predictable, enabling rapid development of production AI workflows.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents often need direct access to enterprise databases such as Snowflake and Postgres, but exposing raw data poses security risks, requires custom API development, and can lead to unpredictable compute costs.
Solution
Pylar provides a middleware layer that mediates between AI agents and data warehouses, allowing teams to define fine-grained data access policies without writing API code. By configuring SQL views or policies, users grant agents only the data they need, while the platform enforces security and monitors usage. The service offers real-time observability across all AI deployments, enabling teams to track queries, performance, and cost metrics. Predictable compute billing is achieved through controlled query execution and resource management. This approach accelerates the creation of production AI workflows and custom tools that safely leverage existing data stacks.
Target Audience
Primary customers are engineering, data, and AI platform teams that need to integrate large language model agents with enterprise data sources while maintaining security and cost control.
Features
- Middleware that connects AI agents (e.g., LangChain, n8n, Cursor) to Snowflake, Postgres, and similar databases
- Granular, policy‑driven data access controls defined via SQL views or rule sets
- No‑code tool generation: agents automatically receive authorized data without custom API development
- Full observability dashboard showing query logs, performance metrics, and cost usage per deployment
- Predictable compute cost management through controlled query execution and resource throttling
- Immediate propagation of data schema changes to connected agents without redeployment