Our AI app gets a lot of repeated questions, can we cache the answers?
Yes, and it is usually the biggest cost saving in a live AI app. Two layers help: prompt caching on the vendor side (Anthropic, OpenAI cache input tokens) and application cache on your side (same question reuses the answer). Together they can mean a 2 to 10 times saving.
Try this first
- 1Detect cacheable questions: a hash over (normalised prompt, model, parameters). A chatbot getting 'what are your opening hours' ten times a day is a perfect cache hit.
- 2Store in Redis, Vercel KV or a small Postgres table with TTL. For factual questions like opening hours or policy, TTL of hours or days is fine, for personal data always none or very short TTL.
- 3Enable prompt caching at the API level where available (Anthropic prompt caching, OpenAI prompt caching). The same system prompt or context block becomes cheaper on follow-up requests.
- 4Monitor hit rate. A good cache hit rate for FAQ-style questions often sits above 30 percent. Below 5 percent your key strategy is probably too strict, fix the normalisation.
- 5Never cache blindly for multi-user inputs with PII or customer context. Include user-id or context-id in the key to avoid leaks between users.
When to bring us in
Want us to add the cache layer to your AI app and measure the saving, we can do it in a day.
See also
- Can I paste a customer file or email into ChatGPT?Depends on the account and settings. Free ChatGPT and a Team tenant behave very differently from what most people assume.
- I want a one-page AI policy for my teamA real one-pager beats a thick document nobody reads. Four headers and concrete examples.
- How do I tell if an AI answer is made up?Models sound confident even when they are wrong. A few habits catch most mistakes.
None of the above fits?
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