Context — 03.1
Infrastructure decisions should follow operating requirements.
AI infrastructure is more than access to a model. A production system may need identity, model routing, retrieval, data pipelines, application interfaces, queues, storage, observability, evaluation, secrets, policy enforcement, and cost controls. Each layer creates dependencies that must be owned after the initial implementation.
Grayhackle begins with workload, data, control, latency, integration, support, and continuity requirements. Those requirements determine whether a managed cloud service, private hosted environment, on-premises deployment, open-source model, or mixed architecture is appropriate. The result may deliberately use more than one provider or execution environment when the operating boundary warrants it.
Integration is designed as part of the foundation. Models and tools must receive the correct context, act through narrow interfaces, and return results to the systems where work is managed. The architecture should make provider changes, degraded modes, and manual recovery possible without rebuilding the entire operation.