Strata gives technical teams a unified platform to deploy APIs, inference workloads, and backend systems into production with visibility, speed, and operational control.
Deploy high-performance inference, orchestrate workloads automatically, route traffic globally, and run on the frameworks your team already uses — without managing the underlying control plane.
Run LLMs, embeddings, and multimodal workloads on optimized compute tiers built for sustained production traffic.
Scale from zero to multi-region capacity automatically, without tuning clusters, queues, or hardware pools manually.
Route requests intelligently across regions to reduce latency, improve availability, and keep performance close to users.
Run PyTorch, TensorFlow, TensorRT, vLLM, and custom model stacks without rebuilding your deployment workflow.
Strata brings deployment, routing, batching, and model orchestration into one unified runtime so technical teams can ship production AI systems without stitching together fragmented infra.
Deploy inference workloads close to demand with region-aware routing, resilient failover, and low-latency execution across Strata’s distributed runtime.
Manage model versions, hardware allocation, image builds, and rollout policies from a single deployment layer designed for production inference systems.
Increase throughput automatically with request batching, queue-aware scheduling, and runtime-level optimizations that improve GPU utilization under live traffic.
Ship APIs, inference endpoints, and backend services through one deployment workflow with built-in routing, autoscaling, observability, and infrastructure-aware execution.
From runtime setup to live observability, Strata gives technical teams a clear operational path to deploy, route, scale, and manage production AI workloads without stitching together fragmented infrastructure manually.
Bring models, APIs, queues, and backend services into one deployment-ready control surface.
Configure compute, regions, scaling rules, and deployment policies before traffic ever goes live.
Roll workloads out across regions through one deployment workflow instead of managing isolated surfaces.
Send requests to the healthiest and closest runtime path using latency- and region-aware routing logic.
Expand active capacity under live inference demand without manually tuning queues, clusters, or hardware pools.
Track runtime health, request flow, regional status, and system activity through one operational view.
Define deployment behavior once and let Strata manage execution across regions and hardware tiers.
Stay informed with real-time metrics for latency, health, throughput, and regional runtime status.
Control compute classes, scaling thresholds, routing rules, and rollout behavior without rebuilding workflows.
Strata is built for teams running live inference, distributed APIs, and regional runtime infrastructure — with reliability, observability, and operational control designed into the platform.
“Strata removed the infrastructure sprawl from our inference stack. We can deploy globally, monitor runtime health, and scale traffic without building a custom control plane around it.”
Regional failover, health-aware routing, and runtime safeguards keep production traffic stable under live demand.
Monitor latency, throughput, queue health, and regional runtime behavior through one unified operational surface.
Deploy across regions, compute classes, and model-serving stacks without rebuilding your delivery workflow.
Runtime health across active regions under sustained production traffic.
Region-aware request routing keeps inference performance close to end users.
Distributed runtime presence for global AI services and backend workloads.
Elastic runtime expansion aligned to live load, queue pressure, and inference demand.
Move from prototype to production with a unified runtime for inference, APIs, and backend services — built for global routing, elastic scale, and real operational visibility.