Cloud & Infrastructure
Infrastructure that makes intelligence affordable to run.
Model serving, GPU orchestration and the cost engineering that keeps intelligent systems economically viable.
Architectural layers
Problem
What problem does this solve?
- Serving costs explode when model traffic is not engineered.
- GPU capacity is scarce and expensive; scheduling matters as much as hardware.
- Teams cannot connect a model change to its cost and latency consequences.
Scope
What CAS builds
- Serving architecture: batching, caching, tiered routing, quantization strategies.
- Training and inference infrastructure with reproducible environments.
- Cost and latency telemetry per feature, per model, per request class.
- Deployment pipelines for models with evaluation gates and rollback.
Architectures
Architectures that may be used
Each links into ModLens, the CAS architecture explorer, where the structure and trade-offs are diagrammed.
Method
How CAS approaches engineering
- Cost is a first-class metric in every architecture decision.
- Serve by task class: not every request deserves the largest model.
- Reproducibility is mandatory: same code, same weights, same result.
Outcomes
What can result
- Per-request economics you can explain to finance.
- Headroom: growth without architectural rework.
- Model releases that are routine, not heroic.
Delivery
What the process looks like
01 · Workload profile
Traffic mix, latency targets, growth, budget.
02 · Serving design
Routing, batching, caching and hardware plan.
03 · Platform build
Reproducible training/serving environments and pipelines.
04 · Optimize
Continuous cost/latency engineering with telemetry.
Preparation
What a client should prepare
- Current or projected inference/training workloads.
- Cloud constraints and procurement realities.
- Latency and availability requirements per use case.
Outcomes depend on data, constraints and integration reality. CAS states assumptions explicitly and reports negative results when evidence demands them.
Discuss cloud & ai infrastructure with an engineer.
Bring the problem; we will bring the architecture, the evaluation plan and the honest feasibility read.