Deploying AI to prod at enterprises is a largely unsolved problem

The text discusses the challenges and potential of deploying AI agents within enterprises, highlighting the limitations of current systems like Anthropic's Model Context Protocol (MCP) and the emerging Agent to Agent (A2A) protocol. While AI agents promise enhanced productivity by automating tasks and facilitating collaboration, their effectiveness is hindered by a lack of access to necessary tools, data, and context, as well as challenges in governance, security, and authorization. Enterprises face difficulties in integrating these agents due to the need for stringent data protection and compliance standards. Credal positions itself as a solution by providing an infrastructure layer that bridges the gap between protocols and enterprise requirements, ensuring AI agents operate securely and effectively within complex organizational systems. The company aims to offer an abstraction layer that supports authorization, governance, and auditability, enabling enterprises to leverage AI technologies more efficiently.