The cost of forgetfulness in AI is unsustainable. The next layer of AI infrastructure must be memory-native.

Memori Labs has built an LLM-agnostic memory layer for the agentic web. Memori intercepts queries across any model, learning from every interaction to reduce redundancy and deliver fast, precise, governed responses. Memori compares each query to historical context and writes back structured memory, creating a self-reinforcing loop of faster, cheaper, and more accurate interactions. With Memori, inference costs will be lowered by up to 95.03%, response times are 10x faster, and all responses are fully traceable.

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