Next Role for AI Agents: Recommending and Acting on Real-Time Choices
Use of AI agents is transitioning from systems that learn from decisions to systems that learn to improve the decision environment
Delivering nearly instantaneous decisions based on rules and predictive analytics; software generates decisions within a business process and reveals insights by analyzing data flowing through processes in real time to create actionable intelligence.
Use of AI agents is transitioning from systems that learn from decisions to systems that learn to improve the decision environment
Modern manufacturing requires more than traditional management strategies, specifically it needs manufacturing data analytics (MDA). However, a recent study …
In 2025, predictive analytics is being widely applied across industries to anticipate events, optimize operations, and personalize experiences in real time.
In this week's real-time analytics news: AWS announced the open source release of Spark History Server MCP, an MCP server that enables AI assistants to access …
In this week’s real-time analytics news: MCP continues to gain momentum with multiple vendor announcements for support of the protocol.
As energy systems become more decentralized, automated, and data-driven, real-time visual intelligence is poised to play a more critical role in supporting …
Organizations that effectively integrate intelligent AI solutions into their core functions, leveraging data and real-time insights, will lead in their …
Cobots are engineered for seamless human-machine interaction, offering advanced motion control, real-time reprogramming, and dynamic task
Real-time threat intelligence, analysis, and prevention arrive with planning, implementation, and cost challenges. However, they could prove essential in the …
The successful adoption of Agentic AI requires real-time and dynamic access to business data. Here, Edward Funnekotter, Chief AI Officer, Solace, discusses how …