Discover Meko: The Data Infrastructure for Agents That Work and Learn Together

Meko is an agent-native data infrastructure designed to address the challenges of building and deploying multi-agent AI applications, particularly focusing on issues like fragmented data systems and the inability of agents to share knowledge and memory efficiently. It provides a unified data layer that facilitates collective memory, shared knowledge, and decision traceability across multiple agents, thereby enabling them to learn together and improve over time. By integrating seamlessly with existing agentic frameworks through a single MCP endpoint, Meko abstracts the complexity of traditional databases and offers a streamlined approach where agents can store and retrieve data efficiently without the need for custom logic or multiple database systems. This approach significantly reduces the costs and latency associated with cross-database queries and manual data management, while also enhancing the auditability and compliance of AI systems by maintaining a comprehensive decision trace that records not only the outcomes but also the reasoning behind agent actions. Built on YugabyteDB, Meko supports seamless integration for real-time and historical data management, ensuring scalability and resilience for production-grade AI systems.