Session Context maintains the state of ongoing interactions between users and AI agents. Unlike simple chat history, session context includes structured state — what the user is working on, what decisions have been made in this session, what preferences have been expressed, and what the current workflow stage is. This enables multi-turn interactions that feel coherent and productive rather than repetitive.
Session context isn't just conversation transcript. It includes parsed intent, identified entities, workflow progress, and accumulated decisions.
Start an interaction in chat, continue it in the dashboard, finish it in a meeting. Session context persists across interaction channels within a defined time window.
Over multiple sessions, the system builds a model of user preferences — communication style, detail level, common tasks — that personalizes interactions without explicit configuration.
Intelligent management of what context is active. Recent, relevant context is prioritized while older, less relevant information is available but doesn't crowd working memory.
Session Context works in concert with other layers in the intelligence stack — each connection amplifying the capability of both components.
Create interactions that feel intelligent and continuous rather than disconnected and repetitive. Users spend less time re-explaining context and more time getting value from AI collaboration.
Discover how Session Context fits into your enterprise intelligence strategy.
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