RedisAI is a Redis module for executing Deep Learning/Machine Learning models and managing their data. Its purpose is being a “workhorse” for model serving, by providing out-of-the-box support for popular DL/ML frameworks and unparalleled performance. RedisAI both simplifies the deployment and serving of graphs by leveraging on Redis’ production-proven infrastructure, as well as maximizes computation throughput by adhering to the principle of data locality.
Important RedisAI features include its auto-batching support and the DAG (as in direct acyclic graph) command. With auto-batching, requests from multiple clients can be automatically and transparently batched into a single request to increase CPU/GPU efficiency during serving.