Redis on Thursday announced its acquisition of Featureform, a framework for managing and orchestrating structured data signals, in a move aimed at addressing developers’ challenges in deploying production artificial intelligence (AI) systems.
The acquisition positions Redis to tackle what the company identifies as a critical bottleneck of delivering structured data to AI models with speed, reliability, and full visibility into operations.
Financial terms of the acquisition were not disclosed.
Modern AI agents require more than large language models alone. They depend on real-time data feeds, historical interactions, and knowledge repositories to function effectively. Redis says the integration of Featureform will streamline the process of providing that contextual information to models during production deployment.
Featureform will be incorporated into Redis’ feature store offering, joining the company’s current AI infrastructure tools including its vector database and Redis LangCache semantic caching service.
The platform will let developers define features as versioned, reusable pipelines and unify training and inference workflows across both batch and streaming data sources. It will also maintain point-in-time correctness for offline model training while serving low-latency features in production environments, according to Redis. Additionally, the system will detect data drift and monitor shifts in feature distributions.
“Adding Featureform immediately allows Redis to serve more AI development use cases with speed and simplicity,” Redis CEO Rowan Trollope said in a statement. “By integrating Featureform’s powerful framework into our platform, we’re better enabling developers to deliver context to agents at exactly the right moment, so they reason, act, and interact accurately and intuitively.”
Simba Khadder, founder and CEO of Featureform, said the combination unites data orchestration capabilities with Redis’ real-time data platform. “Together, we’re building the context engine for AI and agents, enabling developers to deliver the right data at the right time to power the next generation of intelligent systems,” Khadder said.
