RedisAI

Real‑time model management and deployment for ML

AI serving engine for real-time applications

AI creates new data-layer challenges for organizations, including handling the proliferation and complexity of inference data. Requiring no added infrastructure, RedisAI allows you to run your inference engine where the data lives, decreasing latency and increasing simplicity—all coupled with the core Redis Enterprise features.

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Benefits

AI inferencing where your data lives

Enriching AI transactions with reference data can be vastly slower than the AI processing itself. RedisAI minimizes latency by retrieving the reference data directly from the database’s shared memory.

Deploy new models with no downtime or performance penalties

Update models transparently without affecting inference performance. Fully integrated with MLFlow for managing your AI lifecycle.

Serve AI over a robust, scalable, and production-proven platform

With RedisAI you also get all of Redis Enterprise’s features, including high availability (99.999%) and infinite linear scalability without performance trade-offs.

Superior performance

Delivering up to 9x more throughput than other AI model-serving platforms.

Built-in support for all major AI backends

Serve machine-learning and deep-learning models trained by state-of-the-art platforms like TensorFlow, PyTorch, or ONNXRuntime. Run inferences across platforms.

Runs everywhere

Run on CPUs, state-of-the-art GPUs, high-end compute engines, or even tiny Raspberry Pi or NVIDIA Jetson devices.