Recall FAQs

Question 1

How does Recall provide reliability and data persistence?

Accepted Answer

Recall ensures bulletproof reliability with automatic failover and a 99.9% uptime SLA. It utilizes a sophisticated architecture that combines ultra-fast Redis (L1 cache) with persistent Mem0 cloud storage (L2 cache), guaranteeing both speed and data integrity.

Question 2

How does Recall ensure high performance and scalability?

Accepted Answer

Recall achieves lightning-fast sub-5ms p99 latency through intelligent multi-tier caching strategies. It's built for infinite scale, capable of handling millions of requests per second, making it ideal for growing AI applications from prototype to production.

Question 3

Which LLMs and AI frameworks does Recall support?

Accepted Answer

Recall offers drop-in integration with popular LLMs such as Claude and GPT, and widely used frameworks like LangChain and Vercel AI SDK. Its design ensures compatibility with any LLM, providing a versatile memory solution.

Question 4

What makes Recall 'AI-Native' and how does semantic search work?

Accepted Answer

Recall is purpose-built for LLMs, featuring AI-Native semantic search. This allows your AI applications to retrieve relevant memories based on their meaning, not just keywords, providing a deeper and more contextual understanding for improved responses.

Question 5

What is Recall and how does it benefit AI applications?

Accepted Answer

Recall is an intelligent memory layer for AI applications, providing fast, persistent, and scalable memory. It combines Redis caching for sub-5ms latency with Mem0 cloud storage for bulletproof reliability, significantly enhancing LLM performance and context retention.

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