Agent Ecosystem. Memory

Give Every AI Agent a Perfect Long-Term Memory

Persistent short-term and long-term memory layers. Agents remember user preferences, conversation history, and organizational context, forever.

Memory Architecture
Working Memory
Fast · Small · In-context
Episodic Memory
Recent sessions · Structured
Semantic Memory
Long-term · Vector store · Unlimited
Retrieval path: Semantic → Episodic → Working · < 20ms
Memory capacity
< 20ms
Recall latency
Persistent
Across sessions
RBAC
Access control

Overview

What is agent memory?

Without memory, every agent conversation starts from zero. Agent memory gives AI systems a layered store, fast in-context working memory for the current task, episodic memory for recent sessions, and a large semantic vector store for organizational knowledge. When an agent needs context, it retrieves only what's relevant in under 20ms, keeping responses accurate and personalized without bloating the context window.

What's included

Working memory

High-speed in-context storage for the active task window. Agents always have the most relevant information at their fingertips.

Episodic memory

Structured storage for recent interactions and session history, allowing agents to reference and build on past conversations.

Semantic memory

A scalable vector store for long-term organizational knowledge that agents can query by meaning, not just keyword.

Cross-agent sharing

Memory can be shared across agents in a fleet, so knowledge learned by one agent is immediately available to all others.

Memory compression

Automatic summarisation and compression keeps older memories relevant without consuming unnecessary storage or context.

Access controls

Role-based access control ensures agents can only read and write memories within their authorised scope.

How it works

From setup to production

01

Configure

Set memory tier sizes, retention windows, and access policies for each agent role in your system.

02

Connect

Integrate the memory SDK into your agents with a single import. Memory reads and writes happen automatically.

03

Store

Agents write facts, preferences, and events to memory during every interaction. Storage is durable and immediately consistent.

04

Retrieve

On each new interaction, relevant memories are automatically surfaced and injected into the agent's context before it responds.

01

Configure

Set memory tier sizes, retention windows, and access policies for each agent role in your system.

02

Connect

Integrate the memory SDK into your agents with a single import. Memory reads and writes happen automatically.

03

Store

Agents write facts, preferences, and events to memory during every interaction. Storage is durable and immediately consistent.

04

Retrieve

On each new interaction, relevant memories are automatically surfaced and injected into the agent's context before it responds.

FAQ

Common questions

Related

More from this service

Get started

Build agents that never forget

Talk to an expert and get a tailored implementation plan within 48 hours.

Talk to usRequest a demo