Most AI projects should not begin with a model name. They should begin with the constraints of the real workflow.
Before choosing a provider or deploying anything, define five things:
1. The user and the decision the system must support.
2. The data it may access—and the data it must never expose.
3. The acceptable latency, quality, and operating cost.
4. The failure mode when the model is uncertain or unavailable.
5. The human review and audit trail required.
A durable architecture separates the application, model gateway, retrieval layer, data stores, security controls, and observability. This makes it easier to switch models, control spend, test quality, and recover safely when a provider fails.
Good AI architecture is not about adding the most components. It is about making each component necessary, replaceable, and measurable.
HackerAI helps teams turn these constraints into a practical architecture and a working setup. Explore the service options in our Shop or visit HackerAI.sh.