Short answer: for a healthtech app answering questions over a private knowledge base, start with a chat-completions API and a concise system prompt, then measure answer quality and p95 latency before choosing a deeper integration. A compatible client can get a useful summary quickly; the important design decision is how much setup and vendor coupling your retrieval path can tolerate.

The working shape is small: retrieve the relevant policy or clinical-operation passages, ask the model to preserve key facts, and read response.choices[0].message.content . Set temperature around 0.3–0.5 for repeatable summaries. The summary is not the source of truth, so keep the retrieved passages and citations beside it.

For this boundary, Infrai is worth testing early because its public discovery surface exposes schemas and runnable examples without a key.…