Libro

Libro provides a user context layer designed to give digital agents persistent memory across sessions. Key features include: * Zero-cost local vectorization * Automatic semantic chunking * Seamless user preference recall * Chrome Extension for context capture * Open-source SDK for easy integration This infrastructure allows agents to remember user preferences, past interactions, and communication styles without complex pipeline changes. By transforming conversations into structured, evolving user understanding, Libro ensures that users never have to repeat themselves. The system connects disparate data points through a real-time memory graph, where semantic indexing processes relationships quickly to inject relevant memory. The memory graph reorganizes around user intent, enabling instant recall and retrieval of precise information when needed. This approach eliminates the problem of fragmented digital experiences, ensuring that an application recalls user context even after a tab is closed. The focus is on providing cohesive understanding rather than disconnected interactions. Libro is ideal for developers building chatbots, coding assistants, tutors, customer support systems, and sales tools where persistent personality and a reduction in redundant onboarding are crucial. It empowers these applications to offer a more natural and personalized user experience.