Pylar

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Pylar is a secure data access layer designed to bridge the gap between AI agents and your organization's data infrastructure. By acting as an intermediary, Pylar ensures that AI agents interact with your data through governed SQL views, thereby enhancing security, compliance, and operational efficiency. This approach eliminates the risks associated with granting direct database access to AI agents, such as potential security vulnerabilities and compliance issues. Key Features and Functionality: - Governed SQL Views: Define precise data access permissions by creating SQL views that filter sensitive information and implement row-level security. This ensures that AI agents can only access the data you explicitly allow. - AI-Powered MCP Tool Creation: Utilize Pylar's AI capabilities to automatically generate Model Context Protocol (MCP) tools from your defined SQL views. By providing natural language prompts, you can create tools tailored to specific use cases without manual coding. - Multi-Database Integration: Connect seamlessly to various data sources, including Snowflake, BigQuery, PostgreSQL, HubSpot, and Salesforce. Pylar allows you to unify data across these platforms, providing a comprehensive view for your AI agents. - Universal Deployment: Publish your MCP tools once and connect them to any agent builder using a single secure URL and token. Pylar supports multiple frameworks, including LangGraph, Claude Desktop, OpenAI Platform, Zapier, and n8n, ensuring flexibility in deployment. - Built-in Observability (Evals): Monitor and analyze how your AI agents interact with your data through Pylar's Evals dashboard. Track success rates, latency, cost-per-call, and error patterns to continuously refine your governed views and tools. Primary Value and Problem Solved: Pylar addresses the critical challenge of securely connecting AI agents to structured data sources without exposing raw databases or compromising security protocols. By providing a controlled interface through governed SQL views and MCP tools, Pylar enables organizations to deploy AI agents that can access necessary data while maintaining strict governance and compliance standards. This approach not only enhances security but also streamlines the development and deployment of AI agents, reducing engineering overhead and accelerating time-to-value.