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Give AI agents local-first persistent memory, entity profiles, and semantic search.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "distillory" yet — see the docs or source repo.
Use distillory to design a long-term memory workflow for an AI assistant: store user preferences, project context, and past decisions with add; retrieve relevant context with search; generate profiles for key people and project entities with profile; then outline the recommended write and read flow.
A recommended memory architecture for an AI assistant, including what to store, retrieval strategy, profile usage, and tool-calling flow.
I am working on a cross-functional product project. Explain how to use distillory to automatically extract people, requirements, risks, and decisions whenever meeting notes are ingested, creating a searchable project memory. Include example use cases for add, search, and profile.
A project knowledge management plan showing how meeting content becomes long-term memory and how it can later be queried by entity and semantics.
Give me an example of how an AI agent can use distillory to search relevant history before handling a new task, then use profile to summarize the involved customer or system entities, and finally produce a more accurate response strategy.
A clear task-handling example showing how history retrieval, entity profiles, and memory-based reasoning work together.
Give AI coding agents local-first persistent memory management and recall.
Give AI coding agents persistent local shared memory across agents.
Give local-first AI agents persistent memory across tasks and sessions.
Give AI agents persistent memory, secure retrieval, and structured knowledge management.
Give AI agents local-first memory, retrieval, and spaced learning workflows.
Give AI agents local-first persistent memory with secure full-text and vector search.