What is AI Memory?
AI Memory is the ability of an AI system to retain, retrieve, and apply relevant information from previous interactions. It allows the system to understand history, preferences, decisions, relationships, and working context over time.
How does it work?
AI Memory can combine short-term conversational context with longer-term professional and organizational knowledge. Contextual retrieval, semantic search, permissions, and relevance controls help determine what should be recalled for the current situation.
Memory may include:
- Recent conversational context
- Customer and account history
- Previous decisions and commitments
- User preferences and ways of working
- Organizational knowledge and approved content
What does it mean for the user?
The professional does not have to repeatedly explain the same situation or reconstruct the history behind a decision. The system can continue from prior work and bring forward the context that matters now.
What outcomes can it improve?
- Less repeated preparation
- Greater continuity across conversations
- Faster access to relevant context
- More personalized guidance
- More consistent decisions
How does SpikedAI apply AI Memory?
SpikedAI uses permission-aware memory to help a Digital Twin understand the professional, the customer, and the history surrounding each interaction. It brings forward relevant knowledge before a conversation, supports the user during it, and retains important decisions and actions afterward.
How is AI Memory different from storage?
Data storage preserves information. AI Memory determines what information matters, when it should be recalled, and how it can help the user in the current moment.