Semantic LLM Response Cache
A drop-in caching proxy for LLM API calls that returns a cached answer when a new prompt is semantically near a previous one, cutting token spend and latency on repetitive queries without the misses of an exact-match...
- Target market
- Indie devs and small teams running LLM features such as chatbots, summarizers, and FAQ assistants with repetitive query patterns and a token bill they want to cut.
Problem snapshot
What this solves
Indie AI products re-pay for near-identical prompts constantly: users ask the same FAQ ten different ways, agents re-summarize the same doc, and a naive exact-string cache never hits because the wording differs by a word. The result is an unpredictable, climbing OpenAI or Anthropic bill with no easy lever, and rolling your own semantic cache means wiring up…
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