Prompt caching for faster, lower-cost AI apps
PromptCacheAI is a provider-agnostic cache layer that lets your app reuse responses for exact and similar prompts to lower cost and improve speed.
PromptCacheAI vs provider-native prompt caching
How prompt caching works
A simple, explicit flow that gives you full control over your LLM cache and keeps you provider-agnostic.
1) Check the cache first
Send your prompt to /chat. If we’ve seen it, you get the saved response instantly.
2) No hit? Call your LLM
Keep your provider keys and features (streaming, retries, custom params). PromptCacheAI is provider-agnostic and works as an application-layer prompt cache —
- • No lock-in — switch models anytime
- • Full observability of your outbound requests
- • Apply your own safety/PII filters before saving
3) Save the response
Store it with /cache/save using the provided prompt_hash. Next time it’s faster and cheaper, with your configured TTL.
- • Per-namespace TTL controls
- • Per-user isolation & multi-tenant safety
- • Usage metrics and hit-rate dashboards
prompt caching api flow
// 1) Check cache
const { cached, response, prompt_hash } = await pc.fetch('/chat', { prompt, namespace, provider, model });
// 2) If miss, call your LLM (keep your API keys, streaming, and retries)
const live = cached ? response : await llm.generate(prompt);
// 3) Save back to cache (only when miss)
if (!cached) await pc.fetch('/cache/save', { prompt_hash, namespace, response: live });
return live;Why this is better: you keep provider features, secrets, and costs under your control while adding a fast, semantic-aware prompt cache on top.
Provider-agnostic compatibility
Works with all major LLMs — OpenAI, Claude, Gemini, custom LLMs, and more.
Build and test your AI application without burning tokens
PromptCacheAI lets you replay real LLM responses during development. Once a prompt is cached, you can iterate on UI, logic, and flows without making repeated calls to your AI provider.
- • Test UI and workflows using cached responses
- • Run demos without live LLM API keys once responses are cached
- • Avoid surprise token bills during development
- • Safely load-test your app using cached results
Semantic cache
Capture near-duplicate prompts with similarity-aware reuse.
LLM cache
Understand the product category and architecture.
OpenAI alternative
See when app-layer caching beats provider-native limits.
Reduce token costs
Read the cost-reduction use case for production workloads.
Why developers choose PromptCacheAI
- ⚡ Faster apps: Cut response times for repeated calls.
- 💸 Lower costs: Avoid paying for duplicate requests.
- 🧠 Semantic cache: Serve near-duplicate prompts from cache.
- ⏱️ Configurable TTLs: Control cache lifetime per namespace.
- 🔒 Per-user isolation: Namespaces are scoped for safety.
- 🧩 Provider-agnostic: Works with all major LLMs and more.
- ✍️ Revisable cached responses: Revise cached responses in the dashboard so future cache hits return the version you want.
- 🧪 Dev & test friendly: Reuse cached responses to test flows without LLM costs.
Prompt caching API example
curl https://api.prompt-cache.ai/v1/chat \
-H "X-API-Key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"namespace": "support-bot",
"provider": "openai",
"model": "gpt-4o",
"prompt": "How do I reset my password?"
}'Tip: Set a namespace TTL to control how long responses stay hot.
FAQ
What is prompt caching?
Prompt caching means checking whether your app has already solved the same request before sending another call to an LLM.
How is PromptCacheAI different from provider-native prompt caching?
PromptCacheAI is an application-layer prompt and response cache with semantic reuse, namespaces, TTLs, and provider portability.
When should I use an LLM cache?
Use an LLM cache when your traffic has repeated user intent, recurring support questions, stable RAG patterns, or expensive staging and QA traffic.
Does semantic cache replace my model provider?
No. It sits in front of your provider and only reduces duplicate or near-duplicate calls.
Stop paying twice for the same LLM call.
Join developers saving tokens and speeding up applications with PromptCacheAI.