Reduce costs and improve response times by intelligently caching similar queries. From enterprise tools to consumer apps - we're building the infrastructure for AI-native software.
⚡ Accelerate AI, Intelligently.
InferCache provides intelligent caching and routing for AI workloads, reducing costs and improving performance across your entire stack.
Understands when different prompts mean the same thing — not just identical string matches.
Understands that "How do GPTs work?" and "Explain transformers" are the same question. One query serves multiple variations - you only pay once.
Supports OpenAI, Anthropic, Mistral, and local models with intelligent fallback logic.
Reduce LLM spending on repeated queries while delivering sub-10ms cached response times.
Transform your AI operations from expensive and slow to intelligent and efficient.
Your app pays for every repeated query, even if it's just a rephrased version. Costs pile up, latency is unpredictable, and resources are wasted on duplicate computations.
Calls get smartly cached and resolved in milliseconds — at a fraction of the cost. Semantic matching ensures you never pay twice for similar requests.
Drop-in replacement for your existing LLM API calls
# Before: Direct OpenAI call
response = openai.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Explain ML"}]
)# After: Through InferCache (just change the endpoint)
response = infercache.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Explain ML"}]
)Works with your existing code. No refactoring required.
Choose the plan that fits your scale. All plans include semantic caching and multi-model support.
Join companies saving $15,000+ monthly on LLM infrastructure costs
Have questions or want to explore integration? We'd love to hear from you.
🚀 Accelerate AI, Intelligently.