The Data Platform for AI Clouds
Built for neoclouds, sovereign clouds and AI service providers. Silk helps every GPU serve more tokens, gives each agent its own copy of production data in milliseconds, and lets you host the enterprise databases that keep customers with you for years.
Why the Data Layer Decides Who Wins
Raw GPU hours are commoditizing fast. The AI clouds that pull ahead will be the ones that serve more tokens per GPU, host the agent workloads enterprises are rolling out now, and run the production databases hyperscalers have owned for a decade. Each of those depends on the data layer underneath.
The ecosystems AI clouds build on
Four Ways Silk Powers Your AI Cloud
One software-defined platform sits behind all four.
Faster AI inference
A persistent, resilient KV cache tier over NVMe-oF block storage. Reuse context instead of recomputing it, and keep small cache reads from stalling prefill.
Serving density · Time to first token · Accelerated KV cache · AI framework ready
Explore inference →Enable agent sandboxes
Zero-footprint clones of production data in milliseconds, up to 4,000 per volume. Give every agent its own environment without touching the live system.
CSI / Kubernetes · Clone and offload prod · Speed and scale · Security
Explore agent sandboxes →Improve tokenomics
Up to 5× better cost per token with a Silk KV cache tier.³ Faster data keeps GPUs busy, and dynamic scaling means you stop buying capacity for peaks that rarely come.
GPU utilization · Cost per token · Energy
Explore tokenomics →Deliver enterprise workloads
Run the mission-critical databases and data services enterprises buy from hyperscalers today, and compete for the whole account.
Database · Incremental services · Resilience · Multi-tenancy and QoS
Explore enterprise workloads →Performance That Changes the Bottom Line
Measured results, with the test conditions stated.
From a single client
Duplex throughput over one 200GbE NIC, mixed read/write workload.¹
From a single client
Measured in public cloud. Full platform IOPS scales with client count.²
Clones per volume
Zero-footprint, writable clones, created in milliseconds.
Runs Where Your Data Has to Stay
Silk is software, so it runs on whatever infrastructure you choose. Your data and encryption stay inside your borders, and your own team runs the operations.
- Runs on your own servers or on the instances you already operate
- Data stays in-region, on infrastructure you own or contract
- The same platform in every sovereign region you operate
- Telemetry on your terms: opt out of Clarity, run a dedicated instance, or keep it in-region
Your own hardware
Deploy Silk as software on your NVMe servers and turn them into an enterprise-grade block service.
Your cloud instances
Run Silk on provider instances, the same way enterprises run it today on Azure, AWS and Google Cloud.
Kubernetes native
Provision persistent volumes through the Silk CSI driver, inside the platform your tenants already use.
Let's Talk About Your AI Cloud
We work with AI clouds as an OEM, reseller or co-sell partner. Tell us what you're building and we'll show you where Silk fits.
- 1. Single client with one 200GbE NIC, mixed workload of roughly 65% reads / 35% writes. Figure is duplex (read plus write combined); 200GbE is full duplex.
- 2. Single client in public cloud. Full DataPod IOPS is tested across multiple clients and depends on client count and client CPU.
- 3. Silk analysis comparing inference with a KV cache tier against no KV cache.