Cross-Channel Memory
Cross-channel memory is an AI capability that maintains context and conversation history across different messaging platforms, so interactions on one channel inform responses on another.
Cross-channel memory is what separates a truly unified AI coworker from a collection of disconnected chatbots. When you tell Cole in your private WhatsApp chat that you prefer morning meetings, that note is there when you ask Cole to schedule something in your private Slack chat. With Cole, this covers your private chats: notes are shared across them, and each one is given a short list of what you and Cole said in the others in the last 24 hours. Groups are kept apart: a group uses only that group's messages and notes, never your private chats.
Implementing cross-channel memory requires a unified identity system (knowing that the same user is messaging from different platforms), a persistent memory store (saving preferences, context, and conversation history), and intelligent retrieval (surfacing relevant past context when it matters for the current conversation).
This capability is essential for AI coworkers because real work does not happen on a single channel. People switch between apps constantly, and an AI that forgets everything when you change channels is not a coworker - it is a collection of disconnected tools.
How Cole uses cross-channel memory
Cole, Pocodot's AI coworker, leverages cross-channel memory as part of its core capabilities. Working across 6 messaging channels and the apps you connect, Cole applies these concepts to handle real business tasks - from email management and scheduling to research, follow-ups, and team coordination. Instead of learning the theory yourself, you get the practical benefits through natural conversation.
See Cole in actionRelated terms
Persistent Memory
Persistent memory is an AI capability that retains information, preferences, and context across separate conversations and sessions, enabling continuity over time.
Multi-Channel AI
Multi-channel AI refers to AI systems that operate across multiple communication platforms simultaneously, providing consistent capabilities and context regardless of which channel a user chooses.
Context Window
A context window is the maximum amount of text (measured in tokens) that an AI model can process in a single interaction, determining how much conversation history and information it can consider at once.
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See Cole in action
Stop reading about AI - start using it. Cole handles your email, scheduling, research, and more through the apps you already use.