Speed up AI training and inference.
    Maximize your GPU investment

    High-performance caching infrastructure for large-scale AI training and inference workloads.

    Varnish ensures your GPUs always have fast access to the data they need — reducing wait times, cutting unnecessary data transfer costs, and helping you get more out of your investment.

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    Used in production by Fortune 500s, broadcasters, SaaS platforms, and tech infrastructure leaders.

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    Compute has outpaced storage and network

    GPU clusters scale faster than data delivery infrastructure can keep up. The bottleneck is no longer compute availability — it's how fast data reaches GPUs.

    Traditional AI storage solutions prioritizes performance, but at high cost and with less flexibility. Object storage prioritizes cost and scale, but introduces latency, throughput, and compatibility problems. Varnish bridges that gap.

    Varnish tiered storage enables cheap, durable and scalable cold storage, while delivering cached hot data to GPUs at the local speeds compute requires.

    Read more about the challenge →
    AI INFRASTRUCTURE SCALE →CAPACITY

    What is Varnish Tiered Storage?

    Fetch once. Cache locally. Serve at high speed where the workload runs.

    Varnish Tiered Storage sits between your object storage and your compute. It pulls data from cheap, scalable cloud, on-prem or hybrid object storage — once — then keeps the hot data in fast local cache close to compute, served at sub-millisecond latency and ultra-high throughput (terabit-range). Multiple cache tiers let you balance cost and performance across your workload: hottest data lives at the edge, cooler data steps back, scalable origin stays cheap but durable. You pay for fast storage only where you need it, without staggering data-transfer costs.

    Object StorageS3 / GCS / AzureDurableCost-optimizedVARNISH TIERED CACHEYOLO — You Only Load OnceCache ofLast ResortEgress ShieldMid TierPer data center cacheEdge TierHot dataLocal speeds← maximize capacitymaximize performance →GPU ComputeTrainingInferenceFull bandwidth

    ← Swipe to explore →

    Cost benefits

    Cheap, scalable origin storage

    Cloud economics for cold data

    Minimize transport costs

    Reduce repeated origin reads & egress

    Increase GPU utilization

    Shorter training cycles, higher ROI

    Performance outcomes

    Accelerate AI training cycles

    Minimize I/O bottlenecks in training, maximize GPU-time spent on compute and actual training

    Remove Inference Cold starts

    Near-instant startup for data-heavy inference workloads

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    How a global high-frequency trading firm increased GPU utilization while reducing storage cost

    Thousands of GPUsExabyte-scale storageThree globally distributed clusters
    High-frequency trading floor with multiple monitors displaying real-time market data

    Performance gains at massive scale — without adding more GPUs or keeping all data on expensive storage.

    0.0%

    Cache hit ratio

    Reduced origin reads and avoided egress fees.

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    GPU utilization increase

    From 25% to 75%.

    0×

    More effective use of existing compute

    Without investing in more GPUs.

    0%

    Reduction in storage costs

    Through lower-cost storage tiers.

    Our purpose-built storage could not keep our GPUs fed. Varnish Tiered Storage fixed that bottleneck, and cut our storage bill while doing it.
    Global high-frequency trading firm

    Built for real-world AI infrastructure

    AI-scale caching — designed for multi-terabyte datasets and high-throughput parallel reads.

    Enables prefetching and prefill

    Configure Varnish to anticipate and stage data before compute requests it.

    Architecture agnostic

    Works with any S3-compatible or HTTP origin, on commodity infrastructure with low CPU overhead.

    POSIX-compatible access

    Mount cache as a filesystem for workloads that require POSIX semantics without modifying existing pipeline.

    Customizable cache policy

    Fine-grained TTL, eviction rules, and tier promotion logic.

    Built in invalidation, locking, and observability

    Cache hit rates, throughput metrics, and operational controls out of the box.

    Scales across clusters

    Support distributed environment with consistent performance across nodes and regions.

    Designed for demanding industries

    From shared GPU clouds to genomics, telco edge, and autonomous systems, Varnish fits environments where data has to move fast, compute has to stay fed, and storage efficiency still matters.

    Maximize GPU ROI with faster data access for shared training clusters, low-latency model serving, and multi-tenant infrastructure.

    Accelerate sensor-heavy training pipelines and edge model delivery for real-time autonomous systems.

    Enable AI across distributed network environments where low latency, scale, and data control all matter.

    Speed up data-intensive clinical and scientific workflows without compromising control over sensitive data.

    Deliver massive media assets faster for generative AI, rendering, VFX, and production workflows.

    Support large-scale scientific computing and shared AI infrastructure with faster, more efficient access to data.

    Stop wasting
    GPU capacity

    Let Varnish AI eliminate data bottlenecks across your AI infrastructure.

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