Real-Time AI Inferencing — On Live Production Data
Silk enables real-time AI inferencing on live enterprise data – without destabilizing production systems or driving up cloud costs.
Request a DemoReal-Time AI Breaks at the Data Layer
AI inferencing introduces bursty, non-human access patterns – often equivalent to thousands of concurrent users – against the same mission-critical databases that run the business. Traditional infrastructure can’t absorb these spikes without introducing latency, risk, or runaway overprovisioning.
Silk eliminates the root cause: performance tied to capacity and static configuration. As a software-defined SAN and cloud acceleration layer, Silk delivers an unlimited data layer beneath applications so AI, analytics, and transactional workloads can run against the same live production data – each receiving the performance they need automatically.
What Changes With Silk
When AI inferencing is no longer constrained by the data layer:
- AI models consume live, authoritative production data
- Latency remains predictable under inference spikes
- Production systems remain isolated from AI risk
- Cost per inference stays controlled as scale increases
Real-Time AI, Without Disruption
Live-Context Inferencing on Production Data
Run AI models against authoritative, real-time enterprise context.
No Noisy Neighbors Between AI and OLTP
Govern mixed workloads dynamically without contention.
Before Silk
With Silk
Scale AI Without Overprovisioning
Increase utilization while keeping infrastructure spend under control.
Before Silk
With Silk
Enterprise AI That’s Production-Safe by Design
Deploy AI confidently without destabilizing systems of record.
Sentara's AI Initiative Is Enabled By Silk's Faster Performance and Reduced Cloud Costs
Make Live-Context AI Practical — At Enterprise Scale
Real-time AI inferencing doesn’t fail because of models.
It fails when the data layer becomes the bottleneck.
Silk makes live-context AI an architectural outcome—not a science experiment.
Request a Demo