> ## Documentation Index
> Fetch the complete documentation index at: https://docs.platform.nora.my/llms.txt
> Use this file to discover all available pages before exploring further.

# Memory spaces

> Pick the right container for what you want to remember.

A **memory space** is a named container with a fixed type. You create spaces in the workspace, then attach them to Agents.

## The four types, in detail

### Wiki

Human- and Agent-editable notes, retrievable by semantic search. Best for:

* Standing operating procedures.
* Team knowledge that isn't in any external doc.
* Playbooks the Agent should follow.

Notes have a title, body, tags. Editable in the UI. The Agent can also write new notes when granted permission (see [Notes & recall](/build/memory/notes)).

Retention: indefinite unless you configure a TTL.

### Index

A vector store the Agent writes to and reads from. Best for:

* Facts about entities (customers, products, incidents).
* Anything you'd think of as "records" that don't fit the Wiki text-note model.
* Ingested transcripts, emails, chat logs the Agent references.

Each item has a content field (embedded), metadata, and importance score. Retrieval uses the same hybrid search as knowledge collections.

Retention: importance-decayed by default. Highly-important items persist longer; low-importance items decay out.

### Session

Automatic per-conversation memory. The Agent doesn't do anything explicit — every chat message is captured, summarized as the conversation grows past the model's context window, and made searchable.

Best for:

* Chat Agents that need "we talked about X earlier" behavior.
* Multi-turn tasks where earlier turns matter later.

Retention: per-session unless promoted. You can pin an important turn to persist across sessions.

### Evolution

Read-mostly space that auto-populates with patterns from successful improvements. When an improvement to a similar situation was validated and shipped, the pattern lands here so future runs can benefit.

You don't write to Evolution directly — it grows through the improvement workflow. But Agents attached to it get the benefit automatically.

Best for:

* Long-running Agents where you want compounding quality.
* High-volume Agents where the improvement flow generates rich patterns.

Retention: patterns persist while they remain useful (evidenced by re-use). Unused patterns decay after 90 days.

## Creating a space

**Workspace → Memory → New space**.

Configure:

* **Name** — human-readable.
* **Type** — Wiki / Index / Session / Evolution.
* **Default TTL** — for items without an explicit TTL.
* **Retention policy** — hard delete vs. supersede.
* **Access** — which Agents can read, which can write.

## Attaching to an Agent

Agent Inspector → **Memory → Add space**. Pick from workspace spaces. Choose read-only or read/write.

## Naming spaces

Suggested pattern:

* `<Agent role>-<content>` — e.g., `support-customer-history`, `sales-lead-notes`.
* Or `<domain>-<type>` — e.g., `billing-facts`, `product-glossary`.

Consistency helps when you have many spaces.

## Space size and cost

* Wiki / Session: cheap. No embedding cost per item.
* Index: has embedding cost — same rate as document ingest.
* Evolution: managed by Nora; no direct cost.

Storage is included up to plan limits; overage is priced per GB/month.