Private enterprise inference cloud

AI inference economics, inside your boundaries.

servescale.ai helps IT organizations offer cost-effective inference and model-hosting services across cloud, colo, and on-prem infrastructure — with enterprise control, predictable budgets, and unmatched cost efficiency and performance. Not another API endpoint.

Private enterprise inference loop

AnalyzeUnderstand workload, model, and available infrastructure.

OptimizeTransform the workload/model to match the infrastructure.

ObserveWatch performance, learn, and adapt continuously.

Deploy + scaleUse and optimize resources where available.

Optimized for your models on your infrastructure:
power, cost, performance

60%+Inference cost reduction. Continuously optimized for your environment. No need for high-end AI datacenters. Compatible with your enterprise budget processes.

Any environmentPublic cloud, private cloud, colo, on-prem, neocloud, edge. Hardware agnostic. Multiple simultaneous inference runtime support. Fully multitenant.

Your assetsYour models, data, infra, perimeter. We'll make it work within your boundaries, under your control.

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Observe + analyze

Understand workloads, models, utilization, latency, cost, and infrastructure constraints before placing traffic.

Optimize models

Quantize, prune, distill, shard, and test deployment scenarios against your infrastructure and economics.

Route + schedule

Dynamically place requests across GPUs, CPUs, memory, cache, and heterogeneous accelerator pools.

Operate privately

Keep models, data, governance, and operational control inside enterprise boundaries across cloud, colo, and on-prem.

Product

Private inference cloud your IT team can actually operate

servescale.ai packages model serving, optimization, scheduling, routing, caching, virtualization, and operational controls into a self-hosted software appliance for enterprise inference.

Input

Your models

Open-weight, custom, domain-specific LLMs and SLMs. Augmentation, context engineering. Full control over deployment, updates, context, and operations.

Runtime

Your infrastructure

Public cloud, neocloud, colo, on-prem, edge - any combination. Heterogeneous GPUs, CPUs, NPUs, xPUs, virtualized and scheduled without scale-up dependence. In your Kubernetes.

Outcome

Your economics

Predictable budgets instead of uncontrolled per-token spend. Lower ops and infrastructure costs. We monetize waste reduction, not capacity consumption.

Core capabilities

Model serving with multiple concurrent inference runtimes, data augmentation, and context management
Model-aware resource management and dynamic scheduling
Infrastructure- and hardware-agnostic deployment
Multi-tenancy via GPU, CPU, and memory virtualization with SLA/SLO support
Single server to hundreds of racks; federatable across private, public, and neocloud environments

Standard APIs + MCP

Model analyzer

Model optimizer

Model scheduler

Router

Cache plane

Runtime

Virtualization + multi-tenancy

Your infrastructure: K8s, compute, storage, network, xPUs

Your cloud: private, colo, neocloud, public cloud

Product differentiation

Economics-first, model- and topology-aware inference.

The system adapts models to infrastructure and continuously optimizes execution.

Model adaptationQuantize, prune, distill, shard, kernel recompile, test rollbacks, and run A/B deployment scenarios.

Dynamic schedulingModel- and topology-aware scheduling with automatic sharding and continuous optimization. Virtualized GPU, NPU, and CPU resources.

Split prefill / decodeSupport for disaggregated execution and CPU spill for decode when economics make sense.

Fast KV-cacheDistributed, virtualized KV-cache for more efficient serving under enterprise constraints.

Inference runtimesMultiple simultaneous inference runtimes picked to best suit the model, given the user’s performance and cost constraints.

Automated recoveryRuntime designed for resilience, rollback, and operational continuity.

model analyzer + optimizer + scheduler + virtualization =
the economic control plane

Designed for your environment

Designed for your environment.

Built to sit between your applications, data systems, Kubernetes control plane, AI Ops, CI/CD, and infrastructure - without forcing a new cloud, a new stack, or a new operating model.

Your applications, agents, chatbotsstandard OpenAI-compatible and Claude-style APIs
MCP-ready integration points

Your datastorage, databases, context systems
standard APIs and MCP

Your Kubernetes control planeoperators, CRDs, policies, namespaces
fits your existing platform engineering model

Your AI Ops, CI/CD, governanceKubernetes APIs, deployment workflows, observability
change control and operational guardrails

Any infra, anywhereGPUs, NPUs, CPUs, xPUs
bare metal, VMs, containers
multiple inference runtimes
Private cloud, colo, neocloud, public cloud, edge

Standard APIs + MCP

servescale.aiprivate enterprise inference cloud

analyzeoptimizeschedulevirtualize

Your infrastructureK8s, compute, storage, network, xPUs

Your cloudprivate, colo, neocloud, public cloud

AI Ops, CI/CD, governance