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The Output stage is where cleaned, chunked, enriched data becomes retrievable knowledge. Every pipeline must have at least one Output block.

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Output block types

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Document store

Writes chunks into a Nora document collection. This is the default target for most pipelines. Configure:
  • Collection name — new or existing.
  • Write mode — see below.
  • Retention — how long chunks stay after their source is deleted (default: 90 days as tombstones, then removed).
Once written, agents can retrieve from this collection by attaching it as a data source (see Attach data to agents).

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Memory space

Writes chunks or summary facts into a memory space. Choose the space type when creating (Wiki, Index, Session, Evolution — see Memory spaces). Common recipe: run a Foundry pipeline over a chat transcript archive, output as a memory space, and attach that space to your support Agent so it can recall prior conversations.

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Knowledge graph

Writes extracted entities and relationships as graph nodes and edges. Useful for structured domain data. See Causal graph overview.

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External sink

Push results to a system outside Nora:
  • HTTP webhook (POST each chunk).
  • Kafka topic.
  • S3 (as JSONL).
  • Postgres (upsert into a table).
Useful when Nora is producing knowledge consumed by systems you already have.

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Write modes

  • Upsert — write new chunks, update chunks whose content hash changed, leave unchanged chunks alone. Default. What you want in 90% of cases.
  • Replace — clear the collection first, then write everything from this run. Use only for full rebuilds.
  • Append — never touch existing chunks, always write new. Rare — use if you want historical versions accessible.

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Handling deletes

When a source item disappears, Nora emits a delete event. Output blocks default to marking derived chunks as superseded — retrieval skips them, but they remain queryable for audit. Change to hard-delete in the Output block settings if you need it.

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Idempotency

Output writes are idempotent by chunk content hash. Re-running a pipeline against the same source produces the same store state. This lets you rerun freely without duplication.

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Transactions

An Output block’s writes are committed atomically per source item: either all chunks from a given source land, or none do (with the run marked as failed for that item). This prevents partial ingest from leaving your Agents with half-consistent state.

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Split outputs

You can wire multiple Output blocks in parallel — e.g., write to a general document collection and a specialized memory space. Each Output has its own filter — put a filter step upstream if you want different subsets going to different destinations.

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Verifying the write

The Run logs page shows per-Output stats: items written, items updated, items skipped as unchanged, items superseded, bytes stored.