Data, Memory & Knowledge. Memory
Persistent AI Memory Across Every Interaction
AI that remembers your users across every session, preferences, context, history, with sub-20ms recall and RBAC-controlled access to memory namespaces.
Overview
What is persistent AI memory?
Most AI interactions are stateless. Every new conversation starts from scratch, forcing users to re-explain context, preferences, and history repeatedly. Persistent AI memory stores everything learned across sessions in a structured, searchable memory store, so AI assistants remember who each user is, what they're working on, and how they like to work, from the very first message of every new session.
What's included
Cross-session continuity
Memory persists indefinitely across sessions. Users never need to re-explain their role, preferences, or ongoing projects.
Selective recall
On each session start, only the most relevant memories are surfaced based on the current context, keeping the context window lean.
Memory namespaces
Separate memory namespaces for user preferences, project context, and organisational knowledge, each with independent access controls.
Explicit and implicit memory
Users can explicitly save information ('remember that I prefer weekly summaries') or AI infers and stores context from conversation patterns.
Memory inspection
Users can view, edit, and delete their stored memories at any time from a self-service memory management interface.
RBAC and encryption
All memory is encrypted at rest and in transit. Role-based access controls ensure no memory crosses organisational or team boundaries.
How it works
From setup to production
Integrate
Add the memory SDK to your AI application with a few lines of code. Memory reads and writes are handled automatically by the SDK.
Store
During each session, the SDK automatically captures and stores salient facts, preferences, and context in the user's memory namespace.
Recall
At the start of each new session, relevant memories are retrieved and injected into the system prompt before the user's first message.
Refine
Memory relevance improves over time as the system learns which stored facts most frequently improve response quality for each user.
FAQ
Common questions
Related
More from this service
Enterprise RAG
Combine personal memory with organisational knowledge retrieval for richer AI answers.
Knowledge Graph
Connect user memory to the broader organisational knowledge graph for contextual reasoning.
Data Governance
Apply access controls and audit trails to memory data at scale.
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