Continuo Memory FAQs

Question 1

What are the hierarchical compression levels in Continuo Memory?

Accepted Answer

Continuo uses three levels: N0 for raw chunks (code, conversations), N1 for micro-summaries combining 5-10 N0 chunks, and N2 for meta-summaries compressing 5-10 N1 summaries. This structure optimizes storage and retrieval efficiency.

Question 2

Is Continuo Memory expensive to use?

Accepted Answer

Continuo Memory is designed to be cost-effective. It supports 100% local deployment with free open-source embeddings (e.g., Sentence Transformers) or a hybrid low-cost option using providers like OpenAI, ensuring flexibility for various budgets.

Question 3

How does Continuo Memory address LLM context window limits?

Accepted Answer

It separates reasoning (LLM) from long-term memory. By storing knowledge in a vector database with multi-level hierarchical compression (N0, N1, N2), it allows developers to access vast amounts of relevant information without overwhelming the LLM's context window.

Question 4

Can Continuo Memory be integrated with my existing development environment?

Accepted Answer

Yes, Continuo Memory features MCP (Model Context Protocol) integration, allowing seamless connectivity with compatible IDEs like Qoder and Cursor. This enables direct access to memory search, storage, and statistics within your workflow.

Question 5

What is Continuo Memory?

Accepted Answer

Continuo Memory is a persistent memory system for development workflows. It provides semantic search and storage capabilities, leveraging hierarchical compression to maintain knowledge indefinitely and circumvent LLM context window limitations.

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