ContentWise, the AI-powered customer experience leader, has unveiled the ContentWise Agent Engine, an advanced integration of autonomous AI agents and agentic capabilities into its flagship UX Engine platform.
This next-generation enhancement empowers marketing and editorial teams to concentrate on strategic decision-making, while delegating complex, multi-step execution processes to intelligent AI agents – unlocking new levels of efficiency, automation, and scalability.
By incorporating pioneering multi-agent system architectures – including Google’s Agent-to-Agent (A2A) protocol and Anthropic’s Model Context Protocol (MCP) – ContentWise is setting a new standard for smart digital experience management across media, entertainment, and e-commerce industries.
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“Creating and managing truly personalized user experiences at scale is a significant challenge. Teams are often bogged down by complex configuration tasks, manual curation, and the difficulty of interpreting vast amounts of user data and tools to drive KPIs.”
The ContentWise Agent Engine is designed to address this challenge head-on. These autonomous software agents are purpose-built to carry out intricate tasks, make context-aware decisions, and interface with external tools — all based on high-level user-defined goals. Fully integrated into the ContentWise UX Engine, the agents streamline digital operations by shifting from manual, tool-specific configurations to automated, intent-driven processes.
How It Works: Intelligent Collaboration at Scale
The new Agent Engine operates through a multi-agent architecture, where each agent is specialized in a distinct function. For example, a “Pattern Discovery” agent analyzes user behavior trends, while a “UX Configurator” translates overarching business goals into actionable platform settings.
A central host agent coordinates these specialized agents, using industry standards such as Google’s A2A protocol and Anthropic’s MCP. This enables the system to deconstruct complex requests — such as “promote trending shows to the right audience” — into discrete subtasks that are assigned to the most relevant agents, each executing its part collaboratively and efficiently.
“This significant advancement will enable marketing and editorial teams to focus on high-level decision-making while delegating complex execution chains to AI agents, and unleashing a new range of use cases.”
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