ServiceNow is trying to solve one of enterprise AI’s biggest problems: giving autonomous agents enough trusted, real-time context to act inside business workflows. The company introduced Context Engine and Autonomous Data Analytics, new tools designed to connect configuration data, workflow history, operational policies, and third-party systems through a shared semantic layer.
The company expanded its native RaptorDB Pro database by releasing three concurrent processing features called Live Perform, Live Connect, and Live Archive. The underlying engine consolidates operational and analytical workloads onto a single infrastructure tier, which eliminates data pipelines and translation latency for external analytics providers. Additionally, ServiceNow expanded its Workflow Data Fabric through a new partner passport program, consolidating data quality, security, and observability tools from suppliers like IBM and Boomi under a unified enterprise credit agreement.
To regulate autonomous software behavior, the firm introduced the ServiceNow MCP Registry alongside its new AI Gateway to monitor agentic workloads. The private enterprise Model Context Protocol registry integrates with the company’s AI Control Tower, restricting autonomous agents to a vetted internal catalog of approved servers from early partners including GitHub, Box, and Zoom. “The enterprises winning the AI race are bringing trusted, contextual data directly into the workflows that run the business,” stated Gaurav Rewari, Executive Vice President and General Manager of Data and Analytics Products at ServiceNow. Matthew Kritzer, Principal Platform Architect at PayPal, noted that utilizing the platform has made their longest-running operations “five times faster.”