Inference Infrastructure
Serving stacks engineered for latency, cost, and scale.
Inference Infrastructure is the runtime layer behind every Zansoc product: batching, KV-cache management, quantization, speculative decoding, and regional failover. It turns trained models into services that meet SLOs under bursty, multi-tenant traffic.
Runtime Optimization
Kernels and schedulers tuned per accelerator.
Caching
Semantic and prefix caches for repeatable workloads.
Autoscaling
Traffic-aware replicas with warm pools.
SLA Tooling
Latency histograms and error budgets as code.
Latency is a product feature
We profile end-to-end paths from gateway to token, then attack the dominant costs: cold starts, cache misses, and cross-region hops. Inference configs are versioned with the model so rollouts do not silently change performance.
Shared lessons from continental scale
Patterns from our distributed inference case study — routing, caching, failover — are implemented here as reusable modules for Distributed Cloud and product teams.
Safe multi-tenancy
Noisy neighbors cannot steal GPU time or peek at another tenant’s KV cache. Isolation, quotas, and encrypted scratch space are defaults for enterprise deployments.