The Memory Layer for Enterprise AI Agents
Agentic Memory gives OneAI agents continuity across users, workflows, and knowledge - remembering preferences, people, and prior work so no one starts from zero. Extracted automatically, connected in a Work Graph, and governed on every write.
Prefers concise, bulleted summaries · Timezone GST · Replies signed as user
Weekly digest ships Fridays · Briefing skips no-reply & bulk notifications
Grounded in Finance KB v2 & Board decks · Citations required on claims
"the board deck" → Q3 Board Review · linked people, threads & tasks
Stateless AI Forgets. OneAI Remembers Every Context.
Without persistent memory, teams constantly re-explain standing rules and agents lose context after every turn. Agentic Memory preserves user preferences, thread histories, and Work Graph relationships across every workflow.
Personalized Execution
Responses match how each person works - tone, format, timezone, and custom identifiers.
Zero Prompt Redundancy
Standing rules and preferences are captured once and applied automatically across all turns.
Cross-Surface Continuity
Threads, meetings, and tasks remain linked together in a continuous enterprise Work Graph.
Self-Tuning Memory Loop
Feedback overrides tune recall accuracy over time so agents become more reliable every day.
Four Kinds of Memory, One Governed Store
Each type answers a different question about context - and each is isolated per user and tenant.
User memory
Language, formatting preferences, timezone, identifiers, and recurring needs - preferences weighted twice so strong signals win.
Agent memory
Execution patterns, workflow history, and prior task behavior - so the agent picks up where it left off instead of relearning.
Knowledge memory
Retrieval grounded in approved knowledge bases and datasets, with inline citations on every claim.
Connected memory
A Work Graph of people, threads, projects, and commitments - the referent registry that resolves "reply to that one".
How Agentic Memory Works
Memory is extracted automatically as people work - every write passes policy before it's stored, and is reused only where allowed.
Context appears
A preference, decision, or standing rule shows up mid-conversation.
Policy is applied
Governance rules decide what may be stored and at what scope.
It becomes memory
The fact is written to the isolated store and linked to the Work Graph.
Reused later
Recall surfaces it in the right context without replaying stale details.
User Memory
Stores user preferences, formatting requirements, timezone, and standing rules.
Govern Memory Like Code
Admins set policy for what's remembered and what's never stored. OneAI keeps helpful working context - and refuses secrets outright.
- Per-user and per-tenant isolation, always
- Policy-based governance with admin controls
- Every memory is inspectable and auditable
Six Pillars of Memory Governance
Policy-based governance
Rules define what memory captures, and where it applies.
User-level isolation
One person's memory is never visible to another. CBAC-scoped throughout.
Sensitive-data protection
Secrets and regulated data are refused before they reach the store.
Administrative control
Admins review, edit, promote-to-tenant, or delete any memory.
Auditability
Every write and recall is logged and attributable.
Closed-loop feedback
👍/👎 on a memory tunes recall - an override that expires on its own.
Enterprise Compliance & Auditability
"The board deck" resolves to the right thread. Standing rules like test-email recipients just happen. And when memory needs tuning, one tap corrects it.
Drafting a reply to Priya Nair on "Q3 Board Review - deck v2" - concise style applied.
Frequently Asked Questions
Enable Agentic Memory for Your AI Agents Today
Continuity across users, workflows, and knowledge - with governance built in.