Individuals generate vast amounts of personal data across devices and services, but this information remains siloed, making it difficult for AI applications to understand a user's context, preferences, and intent. The lack of a unified, user‑controlled memory layer limits the usefulness of AI assistants and hampers personalized experiences.

Pickle provides a personal memory platform that aggregates a user's spoken words, actions, and learned information into a single, structured memory layer. The system distills raw inputs into standardized episodes, identifies recurring patterns, and makes these memories searchable for any AI service. By recalling relevant episodes in real time, Pickle enables AI assistants to anticipate user intent and take proactive actions. The platform runs within secure enclaves and uses open‑source code, ensuring that the memory data remains under the user's sole control and is accessible only to authorized applications.

Data ingestion pipeline that captures text, voice, and interaction logs from multiple sources and normalizes them into episode records

Pattern‑recognition engine that extracts behavioral and preference trends across the user's history

Intent‑prediction module that retrieves the most relevant memories to inform AI responses and actions

Continuous learning loop that refines memory representations with each new interaction, improving personalization over time

Secure enclave architecture with end‑to‑end encryption, guaranteeing that memory data is stored and processed locally under user ownership

Open‑source SDK and APIs that allow third‑party AI models to query the memory layer without exposing raw user data

Pickle is aimed at developers of personal AI assistants, productivity tools, and any applications that benefit from deep user context, as well as privacy‑conscious consumers who want a single, sovereign memory repository.