Real-Time AI Inferencing at Enterprise Scale

Run AI Inference on Live Data — Without Breaking Production

As AI pilots move into production, many organizations discover their infrastructure can’t keep up. AI inference workloads create intense bursts of I/O, high read concurrency, and extreme sensitivity to latency — conditions traditional storage systems were never designed to handle. The result is unpredictable performance, rising infrastructure costs, and workarounds like replicas and ETL pipelines that introduce data lag. Silk solves this by providing a software-defined SAN built specifically to deliver live operational data to AI inference workloads at enterprise scale — without disrupting existing systems or requiring application changes.

• Deliver real-time data to AI systems with instant database clones that eliminate ETL pipelines and stale replicas.
• Maintain deterministic performance under extreme concurrency with adaptive I/O that automatically optimizes throughput for mixed workloads.
• Scale inference demand without overprovisioning infrastructure, keeping response times stable and reducing cost per inference.