ContentWise Introduces Advanced AI Agents in its UX Engine to Automate and Hyper-Personalize Digital Customer Experiences

ContentWise Introduces Advanced AI Agents in its UX Engine to Automate and Hyper-Personalize Digital Customer Experiences

ContentWise, the AI-powered customer experience company, announced the integration of advanced AI agents and agentic capabilities into its flagship UX Engine platform, introducing the ContentWise Agent Engine.

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.

Leveraging cutting-edge multi-agent architectures, including Google’s Agent-to-Agent (A2A) protocol and Anthropic’s Model Context Protocol (MCP), ContentWise is pioneering a new era of intelligent digital experience management.

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.

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ContentWise’s new AI agents are autonomous software units designed to perform tasks, make decisions, and interact with the digital environment based on user-defined goals. Integrated directly into the ContentWise UX Engine, they connect to a range of external tools and services, empowering teams to move from manual configuration to automated, goal-oriented, multi-step instructions.

How It Works

ContentWise Agent Engine uses a multi-agent architecture with specialized agents for different tasks, such as a “Pattern Discovery” agent for analyzing user behavior, and a “UX Configurator” for translating goals into platform settings.

A host agent orchestrates these specialized agents using industry standards like Google’s A2A protocol and Anthropic’s Model Context Protocol. This allows complex requests, such as “promote trending shows to the right audience,” to be broken down into sub-tasks that are executed collaboratively by the most suitable agents.

SOURCE: PRWeb