SGNL is revolutionizing enterprise security by introducing support for the Model Context Protocol (MCP), which empowers AI agents to take on real tasks while maintaining access controls. As AI technology advances, it brings both productivity gains and new risks, especially regarding sensitive data exposure. SGNL’s innovative platform ensures that AI agents operate within secure boundaries ...
SGNL is at the forefront of secure AI-driven automation, introducing a new standard called Model Context Protocol (MCP) that enhances how AI agents interact with enterprise systems. While these AI agents can significantly boost productivity by performing tasks with simple prompts, they also pose access risks if not properly managed. SGNL’s powerful platform ensures that ...
SGNL has introduced new support for the Model Context Protocol (MCP), an emerging standard that allows AI agents to perform real tasks within organizations. While these agents can enhance productivity, they also pose risks by potentially accessing sensitive information without proper controls. To address this, SGNL offers advanced identity management solutions that ensure real-time, context-aware ...
SGNL has announced its support for the Model Context Protocol (MCP), a new standard that allows AI agents to interact with real-world tools while enhancing security for enterprises. As AI agents gain capabilities to perform tasks across systems with just a prompt, they also present risks due to potential uncontrolled access to sensitive data. SGNL’s ...
SGNL has announced its support for the Model Context Protocol (MCP), which enhances AI agents’ capabilities in enterprise environments. While MCP empowers these agents to automate tasks like data analysis and record updates, it raises concerns about access risks. Without adequate controls, these agents can unintentionally access sensitive information. SGNL’s platform addresses this by implementing ...
SGNL has announced support for the Model Context Protocol (MCP), enabling AI agents to work with real-world tools while maintaining enterprise control. As AI-driven automation gains momentum, these agents can perform tasks like updating records and analyzing data through simple prompts. However, this increased capability comes with access risks. Without strict oversight, AI agents may ...
