AI agents promise enormous potential gains for enterprises: enhanced decision-making through data-driven insights, 24/7 operations without human limitations, and scaled expertise across the organization. However, these transformative benefits will remain unrealized if enterprises cannot trust and verify agent behavior when interacting with operational systems. The challenge is not just technical capability—it's about building the proper methodologies for exposing data from operational systems and the solid frameworks needed to run agents safely in production environments.

Here we focus specifically on system interaction and governance - one critical component of the broader production challenge. While retrieval-augmented generation (RAG) addresses knowledge access with its own security models, we examine a different challenge: how AI agents can securely interact with enterprise systems - databases, APIs, external services, and operational tools - while maintaining auditability, policy compliance, and data integrity.

We propose a conceptual framework for an infrastructure layer designed to address these agent-to-data interaction challenges. The framework is composed of two core components: a secure, auditable Model Context Protocol (MCP) Server for system access, and a Policy-Aware Execution Engine for real-time governance. By decoupling the AI agent from direct system access and enforcing policy at the infrastructure level, this approach provides a viable path for deploying AI systems that can safely interact with enterprise systems while maintaining the trust and verification that enterprises require.

We present both the framework and its practical implementation through MXCP - a production-ready MCP server that addresses these challenges with enterprise-grade features.

We're excited to announce our strategic partnership with Squirro, a leader in enterprise search and AI solutions. Through this collaboration, RAW Labs' technology will power operational data access within SquirroGPT, enabling real-time connections to databases, SaaS services, and other operational systems.

Traditional websites are facing an existential challenge. Not immediately, but the shift is undeniable.

For three decades, the web has been a collection of pages. Click, scroll, search, repeat. It's an interaction model we've accepted despite its inefficiencies.

But a fundamental shift is underway. Instead of browsing through pages, we're beginning to converse with our systems. And they're responding intelligently.