Redis Labs, the home of Redis and provider of Redis Enterprise, is releasing RedisAI and RedisGears, transforming Redis Enterprise into a low-latency, real-time data platform for infinite processing capabilities.
“We’ve heard the challenges customers have as they move AI into production, in particular, the end-to-end AI serving time, which in many cases was influenced by the time it takes to collect, prepare, and feed the data to the AI serving engine. RedisAI and RedisGears were designed to solve this problem, by reducing the end-to-end AI serving time to milliseconds,” said Yiftach Schoolman, CTO and co-founder at Redis Labs. “With Redis Enterprise as the perfect high-performance and scalable foundation, RedisAI and RedisGears will enable our customers to successfully utilize AI technologies to create operational efficiencies and solve real business problems in real-time.”
RedisAI (co-developed by Redis Labs and Tenserwerk) is the answer to the challenge every architect or developer faces as they attempt to design and implement AI in their production applications: the time spent outside the AI inference engine to collect and prepare the reference data.
With the AI serving engine inside Redis, RedisAI reduces the time spent on these external processes and can deliver up to 10x more inferences than other AI serving platforms and at a much lower latency.
Many of the leading AI-driven applications such as fraud detection, transaction scoring, ad serving, recommendation engine, image recognition, autonomous vehicles, and game monetization will achieve better business outcomes with these performance improvements.
Integrated with MLflow, RedisAI eases the management of the AI lifecycle by allowing running models to be updated seamlessly and without downtime.
With built-in support for major AI backend systems (TensorFlow, PyTorch, and ONNX Runtime), RedisAI allows inferencing to be run across platforms.
RedisGears is a new serverless engine for infinite programmability options in Redis. RedisGears enables transaction, batch, and event-driven operations to be processed in milliseconds by performing these functions close to the data—all within Redis.
Additionally, RedisGears allows developers to perform any type of operation across Redis’ data structures and modules. RedisGears functions can be developed once and used across any type of Redis deployment: open-source, Redis Enterprise software, or Redis Enterprise Cloud.
For more information about these releases, visit https://redislabs.com/.