MadTech announced the launch of MadConnect for Agentic Marketing and Advertising, the industry’s first intelligent infrastructure layer purpose-built to enable AI agents to operate across platforms. With native support for Model-Context Protocols (MCPs), MadConnect transforms large language models (LLMs)—including Amazon Bedrock, OpenAI, and Google Gemini—into intelligent agents that can execute real-time marketing tasks, sync audiences, optimize media spend, and generate insights with speed, security, and confidence. Agents built by MadTech, developed in-house, or created by third parties all run natively on MadConnect, creating the essential operational layer that unifies AI, LLMs, and the fragmented AdTech and MarTech landscape.

MadConnect for Agentic Marketing and Advertising is solving platform-to-platform connectivity challenges, defining a new category of intelligent infrastructure where agents interact autonomously across tech stacks with speed and precision for ROI.

This launch comes at a critical moment. Enterprises have an unprecedented opportunity to transform their marketing and advertising operations through the use of AI. With many organizations leveraging up to 120 different AdTech and MarTech platforms, there is a growing need for greater connectivity and orchestration. While these tools offer powerful capabilities, unlocking their full value requires seamless integration. Unified systems can break down data silos, streamline workflows, and enable faster, more accurate, and scalable campaign execution. Rather than relying on costly and time-intensive custom integrations, businesses are now seeking smarter, more agile solutions that free engineering teams to focus on innovation and growth.

“Agentic AI represents a seismic shift in how marketing gets done, less manual coordination, more intelligent execution. What MadTech has built with MadConnect is not just timely, it’s foundational,” said Karsten Weide, Chief Analyst, W Media Research. “For the first time, we have an infrastructure layer that allows AI agents to work fluidly across the fragmented marketing stack, turning disconnected tools into coordinated action. This is how AI becomes operational in the enterprise, not by replacing marketers, but by removing the operational drag that limits them.”

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Already integrated with key platforms such as Salesforce, Meta, Adobe, The Trade Desk, and DV360, MadConnect is uniquely positioned to become the only infrastructure layer the industry needs, making existing tech stacks fully accessible and operable by LLMs and AI agents. Key use cases and capabilities of Agentic AI powered by MadConnect include:

• Creating and syncing audience segments across activation platforms
• Querying and analyzing data at rest to generate real-time reporting insights
• Optimizing media and performance through natural language orchestration by intelligent agents
• Connecting your entire MarTech stack with agent-to-agent communication via one-time integration, maintaining full control over your data, agents, and outcomes
• Deploying securely in your preferred environment, such as AWS or Snowflake, with a SOC 2-compliant architecture

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“MadConnect was purpose-built for platform-to-platform connectivity, and we’ve made it AI-native,” said Bob Walczak, CEO of MadTech. “Legacy players don’t have the modern architecture required to power agentic marketing, at scale. Now, organizations can focus on agentic innovation, not building infrastructure.”

As AI rapidly reshapes the marketing landscape, the expectations for performance, agility, and automation are changing. The interface is evolving from SaaS-based dashboards to natural language; the architecture is shifting from data pipelines to zero-transfer systems; and the business mandate is clear: increase outcomes, not tech debt and overhead.

With the launch of MadConnect for Agentic Marketing and Advertising, MadTech is not just solving platform-to-platform connectivity challenges. It’s defining a new category of marketing infrastructure, one where intelligent agents interact seamlessly across tech stacks and platforms, data is securely accessed where it lives (in motion or at rest), and execution occurs continually and on demand.