Reltio Announces Google Agent2Agent Protocol Support to Fuel Enterprise AI at the Edge

Reltio, a leader in real-time data intelligence, announced its support of Google’s Agent2Agent (A2A) protocol, furthering its strategic role in enabling interoperability among autonomous enterprise AI agents.

Adopting A2A enhances its recently launched Reltio AgentFlow, a fully managed, enterprise-grade solution that provides secure, real-time connectivity between trusted enterprise data and AI agents. Reltio AgentFlow supports MCP and A2A protocols, which are complementary to each other, according to the company.

The A2A protocol establishes a standardized framework for autonomous agents to securely communicate, exchange structured data, and coordinate complex workflows, eliminating the need for manual integration or proprietary connectors.

Using A2A demonstrates Reltio’s ability to deliver enterprise-grade, real-time data readiness and seamless interoperability required for scaling AI-driven operations, the company said.

"AI initiatives often stall because companies find that their agents lack real-time access to unified, trustworthy data,” said Manish Sood, CEO and founder of Reltio. “By enhancing Reltio AgentFlow with Agent2Agent interoperability, we are uniquely positioned to help companies break through these barriers delivering immediate value by enabling organizations to operationalize AI rapidly, securely, and at scale."

Reltio AgentFlow, with support for A2A and MCP protocols, empowers enterprises to seamlessly connect large language models (LLMs) (such as the ones from OpenAI, Anthropic, or Google Cloud), AI agents and frameworks (such as LangChain, CrewAI, and others) directly to governed, real-time data from the Reltio Data Cloud.

Unlike static data snapshots or cumbersome, custom-built API integrations, Reltio AgentFlow Server offers plug-and-play connectivity, significantly accelerating AI deployment and adoption, according to Reltio.

Key benefits include:

• Rapid AI Deployment: Move from concept to operational AI workflows in hours, not weeks, eliminating the need for custom API development.
• Interoperability and Flexibility: Seamlessly integrate diverse AI agents and easily swap or scale agents and LLMs without vendor lock-in or rebuilding integrations.
• Operational Efficiency: Automate routine data management and business tasks, such as deduplication, enrichment, and compliance checks through AI-powered agents.
• Enhanced Decision-making: Enable AI agents to deliver accurate, context-rich insights based on live, trusted data, improving outcomes across sales, marketing, supply chain, and customer support.
• Reduced Compliance Risk: Supplied with built-in robust security, including OAuth, role-based access control (RBAC), and audit logging, allows secure data usage without additional security infrastructure.

Business use cases include:

• Sales Automation: Prioritized leads and qualified opportunities delivered via AI agents in real-time using live customer data.
• Marketing Optimization: Autonomous personalized campaign activation based on current customer behavior.
• Supply Chain Intelligence: AI-driven, real-time supplier data monitoring and logistics planning.
• Customer Support Enhancement: Real-time recommendations and support insights leveraging complete customer profiles.
• Data Team Productivity: AI-assisted deduplication, enrichment, and governance significantly enhance data quality and operational efficiency.

For more information about this news, visit www.reltio.com.