Inference & GPU Platforms
The platform
around the model.
Multi-tenant inference and GPU services on NVIDIA, AMD and other accelerators, on a cloud and Kubernetes platform we build and operate.
What we deliver
Every request routed,
metered and traced.
Infer8 is the platform around your models and accelerators: tenancy, routing, metering, billing and day-2 operations.
Three ways to buy: Infer8 Blueprint (a validated design, typically in 6–12 weeks), Infer8 Stack or Infer8 Cloud.The Infer8 stack
From accelerator to invoice.
- AcceleratorsNVIDIA, AMD Instinct, cloud GPUs01
- Kubernetes platformCloud or bare metal, managed with GitOps02
- Model servingvLLM, SGLang, TensorRT-LLM, Triton03
- RoutingQueues, free-slot gating, circuit breakers04
- Metering & billingOne record per request, with stage-by-stage timings05
- API & consolesOpenAI-compatible API, operator and customer consoles06
What you take away
- 01
An API customers already know
OpenAI-compatible endpoints. Customers switch by changing a base URL.
- 02
Tenancy and routing
Per-customer keys, grants and rate limits. Queues, reserved workers and graceful drain.
- 03
Metering you can bill from
One record per request: identity, model, outcome, stage timings, bytes and tokens.
- 04
The platform underneath
Kubernetes, GitOps, Terraform and observability on AWS, Google Cloud, Azure or bare metal.
Technologies we work with
Chosen for your requirements and your existing environment.
How we work
Built in stages.
Operated 24×7.
The team that builds it runs it, from the first decision through ongoing operation.
- 01 / Define
Agree the outcome.
Scope, constraints and success measures.
- 02 / Build
Build it as code.
Infrastructure, data or AI, in working stages.
- 03 / Validate
Prove it on real work.
Real workflows, real traffic, a rehearsed restore.
- 04 / Operate
Run it 24×7.
Monitoring, on-call, upgrades and improvement.
In production
One platform,
run by us.
An inference platform we designed, built and operate, for an AI API provider serving two of India’s largest consumer-internet apps.
Production inference at scale.
A production inference platform behind a commercial AI API. Two scheduling models in one fleet: an in-house device plugin and Kubernetes DRA.
Explore the projectYour next step
Live in two weeks.
Not 12 to 18 months.
Forty-five minutes on your workload, environment and constraints. You leave with a proposed first step.

