# Your first memory, with a source.

A small, private namespace is enough to begin. Use a disposable example before importing anything sensitive.

## 1. Sign in and select a workspace

Open the workspace and sign in with an email code. An enrolled pilot identity can create a workspace; existing members can select their authorized workspace. If access has not been granted, ask your pilot administrator. Signing in does not enroll you.

## 2. Create a namespace

Create a namespace such as Project notes. Give collaborators only the capabilities they need. Ordinary agents should usually receive read and observe; verification, correction, deletion and administration are separate capabilities.

## 3. Record evidence and a candidate

Add a source locator and the exact supporting excerpt. Save the observation as a candidate and choose when it began to apply. Keep verification separate until an authorized reviewer can attest to the exact text and its evidence.

## 4. Read it back

Open the saved memory directly to inspect its source and time intervals. Recall may report pending indexing after a write. When recall is pending, choose “Search without waiting for indexing” to request bounded retrieval without the saved-write indexing guarantee. If hybrid search is unavailable, retrieval uses a lexical slice. Keep its degraded or partial status; these results do not prove that no matching memory exists.

## 5. Try a historical view

Set both time controls in the workspace. After an authorized correction, compare the earlier known-at cutoff with the current one while holding as-of fixed. The temporal guide includes the exact Boston/New York fixture.

## 6. Connect code or an agent

Use REST for application calls or the MCP resource for a compatible client. Generate requests from the published catalog rather than guessing payloads. Every mutation needs an Idempotency-Key. Tokens are credentials, not permission to choose an arbitrary workspace.

> Do not paste private evidence, tokens or workspace data into public issues, SEO artifacts or shared screenshots. Production and preview storage and identities must remain separate.

## Continue reading

- [Temri · Memory with a sense of time](https://temri.ai/): Shared temporal memory for products and agents. Keep source-backed facts in protected namespaces and distinguish what applied then from what was known then.
- [How Temri works · From evidence to memory](https://temri.ai/how-it-works): Follow a memory from its source to a candidate, verification, historical retrieval, correction and deletion receipt.
- [Developer documentation · Temri](https://temri.ai/docs): Connect to Temri through REST and MCP. Learn workspace permissions, evidence, temporal queries and bounded retrieval.
- [The two clocks · Temri temporal semantics](https://temri.ai/docs/temporal): Understand as_of and known_at, half-open intervals, correction history, server-owned recorded time and deletion suppression.
- [REST API · Temri developer docs](https://temri.ai/docs/api): Authenticate Temri REST requests, select authorized workspaces, use mutation idempotency and handle pending, denied and partial results.
- [Connect an agent · Temri MCP docs](https://temri.ai/docs/mcp): Connect to Temri’s authenticated MCP resource with narrowed scopes. Discover operations and verify your client before sharing memory.
- [Privacy, retention and deletion · Temri](https://temri.ai/privacy): What Temri stores, which services process it, how namespace access works and what a deletion receipt does and does not cover.
- [Pilot terms · Temri](https://temri.ai/terms): Terms for Temri’s admin-managed pilot, responsible use, source-backed claims, service limitations and account access.

[OpenAPI](https://temri.ai/openapi.json) · [Workspace](https://temri.ai/app)