Yugabyte targets the missing memory and knowledge layer for enterprise AI agents
Enterprise investment in agentic artificial intelligence is accelerating, but the infrastructure supporting those systems is still catching up.
Organizations are moving agents into customer support, software development, sales operations and other production workflows. Yet many of those agents remain stateless, unable to retain durable context, share knowledge with other agents or explain how previous decisions shaped current outputs. That gap is becoming less of a model problem and more of a data architecture problem.
In the latest episode of theCUBE Research’s AppDevANGLE podcast, I spoke with Karthik Ranganathan, co-founder and chief executive officer of Yugabyte, about the company’s launch of Meko, a new data infrastructure platform designed to provide persistent memory, shared knowledge and traceability for multi-agent systems.
“Your agentic systems are only as good as the state and the data that you feed them,” Ranganathan said. “The model problems are getting solved really well, and the orchestration problems are getting really good. It’s now the iteration cycles between your data and data infrastructure.”
