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AI Backend Layer — Model APIs, Tool Calls, Logs, and Cost Control

One backend layer for AI calls, tools, logs, and costs

AI Backend Layer case study preview

THE CHALLENGE

Many AI features start as direct calls from the app to a model API. That works for a prototype but breaks when users, roles, errors, cost limits, privacy, and support debugging become real.

OUR APPROACH

We build an AI backend layer between the product and the models. It handles request shaping, tool permissions, schema validation, streaming, fallback models, usage logging, rate limits, and admin visibility.

THE RESULTS

Product teams get a cleaner path to ship AI features without turning the main app into a pile of one-off prompts. This is where AIOVIX sits best: practical AI engineering for teams past the toy-demo stage.