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

# Knowledge Processing

> Endpoints for building and removing knowledge graphs

These endpoints transform raw data into structured knowledge graphs and remove data from them.

## Cognify

**`POST /api/v1/cognify`** — Transform datasets into structured knowledge graphs.

Takes uploaded data and runs entity extraction, relationship detection, and embedding generation. This is the same pipeline described in [Cognify](/core-concepts/main-operations/legacy-operations/cognify).

```bash theme={null}
curl -X POST https://your-tenant.aws.cognee.ai/api/v1/cognify \
  -H "X-Api-Key: your-key" \
  -H "Content-Type: application/json" \
  -d '{"datasets": ["my_dataset"]}'
```

Processing runs asynchronously. Check progress with the [dataset status](/cognee-cloud/functionality/dataset-management#dataset-status) endpoint.

<Note>
  If you used [`remember`](/cognee-cloud/functionality/data-ingestion#remember) to ingest data, cognify was already executed automatically. You only need to call cognify separately when using the `add` endpoint.
</Note>

## Forget

**`POST /api/v1/forget`** — Remove data from the knowledge graph.

Deletes specified content from the graph, vector store, and associated metadata. See [Forget](/core-concepts/main-operations/forget) for the underlying operation.

```bash theme={null}
curl -X POST https://your-tenant.aws.cognee.ai/api/v1/forget \
  -H "X-Api-Key: your-key" \
  -H "Content-Type: application/json" \
  -d '{"data": "content-identifier", "dataset_name": "my_dataset"}'
```