Why Pylar?

​

Why Choose Pylar?

Pylar solves critical challenges in AI agent development by providing a secure, governed data access layer. Here’s why organizations choose Pylar over building custom solutions or giving agents direct database access.

​

Security & Governance First

​

Fine-Grained Access Control

Unlike direct database connections, Pylar lets you define exactly what data agents can access at the view, column, and row level. This means you can:

• Restrict Sensitive Data: Automatically mask or exclude PII, financial data, or other sensitive information
• Row-Level Security: Control access based on user context, regions, or business rules
• Query Validation: Prevent unauthorized queries before they reach your database
• Audit Every Access: Track who accessed what data and when

​

Compliance Ready

Pylar helps you meet regulatory requirements out of the box:

• Complete Audit Trails: Every query is logged with full context
• Data Lineage: Understand where data came from and how it’s used
• Access Controls: Enforce policies that meet SOC 2, GDPR, HIPAA, and other standards
• Documentation: Auto-generated documentation for compliance reviews

​

Developer Experience

​

AI-Powered Tool Creation

Instead of writing custom integrations, use natural language to create MCP tools:

• Natural Language Prompts: Write “create a tool to fetch error codes, events, and deal information” and Pylar’s AI configures it
• Manual Control Available: Fine-tune tools manually when needed
• Multiple Tools Per View: Create different tools on the same view for flexibility
• Test Before Deploy: Verify tools work correctly before publishing
• Standard Protocol: Uses MCP, the emerging standard for AI tooling

​

One View, Multiple Tools

Create multiple MCP tools on a single view, each governing how agents interact with your data differently. All tools work with any MCP-compatible agent:

• Claude Desktop
• Cursor
• Windsurf
• Custom agent frameworks
• Any MCP-compatible tool

​

Rapid Iteration Without Redeployment

• Adjust Anytime: Update queries, view scope, or tools on the platform
• Automatic Propagation: Changes reflect everywhere automatically—no redeployment needed
• Test Before Publish: Test MCP tools before deploying to ensure they work
• Iterative Improvement: Use Evals insights to refine views and tools continuously

​

Operational Excellence

​

In-Depth Evals & Observability

Click “Evals” to get comprehensive insights into how agents interact with your views:

• Interaction Patterns: See exactly how agents use your tools
• Success vs. Errors: Track successful queries and identify failures
• Error Analysis: Detailed breakdown—what errors occurred, when, and why
• Query Shape: Understand the types of queries agents are making
• Raw Logs: Access full query logs for debugging
• Iterative Optimization: Use insights to adjust view scope and tool configurations

​

Scalability Without Headaches

Pylar scales with you:

• Multi-Database Support: Connect to BigQuery, Snowflake, PostgreSQL, and more
• Cross-Database Joins: Join data across multiple databases in a single query
• Project Organization: Organize views and tools in projects for better management
• SQL IDE: Built-in SQL editor for easy query development
• Views Are the Only Access: Agents never get raw database access—complete security

​

Cost Efficiency

​

Reduce Development Time

Building custom agent integrations typically takes weeks or months. With Pylar:

• Days Instead of Months: Get your first tools running in hours
• No Maintenance Burden: Pylar handles protocol updates and compatibility
• Focus on Value: Spend time on your business logic, not infrastructure

​

Lower Infrastructure Costs

• Connection Efficiency: Shared connections reduce database load
• Query Optimization: Built-in query analysis and optimization
• Caching Layer: Reduce redundant queries and costs
• Resource Management: Prevent runaway queries that spike costs

​

Real-World Benefits

​

For Data Teams

• Self-Service with SQL IDE: Use the built-in SQL IDE to create views without waiting for engineering
• Cross-Database Analysis: Join data across warehouses without complex pipelines
• Governance Without Friction: Maintain control—views are the only access level
• Evals Insights: Understand exactly how agents interact with your data
• Iterative Improvement: Use evals to continuously refine views and tools

​

For Engineering Teams

• No Custom Integration Code: AI-powered tool creation eliminates boilerplate
• Standardization: One platform for all agent data access needs
• Faster Shipping: Get agents to market faster with instant tool creation
• Easier Debugging: Evals provide raw logs, query shapes, and error analysis
• No Redeployment: Changes reflect automatically everywhere

​

For Organizations

• Complete Isolation: Views are the only access level—agents never get raw database access
• Risk Reduction: Eliminate direct database access for AI agents
• Faster AI Adoption: Remove blockers with AI-powered tool creation
• Compliance Confidence: Meet regulatory requirements with built-in controls
• Cost Control: Monitor and manage data access costs through Evals
• Iterative Optimization: Continuously improve based on real agent behavior

​

Comparison: Pylar vs. Alternatives

​

Pylar vs. Custom Integration

​

Pylar vs. Direct Database Access

​

When Pylar Makes Sense

Pylar is ideal if you:

• ✅ Have AI agents that need structured data access
• ✅ Need to maintain data governance and compliance
• ✅ Want to avoid writing custom integration code
• ✅ Need visibility into agent data usage
• ✅ Work with multiple databases or data sources
• ✅ Want to scale AI agent usage safely
• ✅ Need to support multiple agent frameworks

​

Getting Started

Ready to experience these benefits? Check out our Quick Start guide to get up and running in minutes.

Start Building

Get your first Pylar tools running in minutes