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Filtering gets you a candidate pool. Ranking picks the winners. Nora exposes several levers.

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Fusion weights

The primary knob: how much to trust vector vs. keyword.
  • Vector weight (0.0-1.0) — dense semantic similarity.
  • Keyword weight (0.0-1.0) — BM25 lexical overlap.
Weights are relative, not absolute — 0.7/0.3 behaves the same as 0.35/0.15. Adjust to shift emphasis.

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Boosts

Recency boost, tag boost, source boost. All optional, all multiplicative on the fused score.

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Recency boost

Newer content ranks higher. Two forms:
  • Decay — half-life in days. Older chunks score lower on a smooth curve.
  • Hard cutoff — chunks older than N days are excluded entirely (better as a filter than a boost, honestly).

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Tag boost

Boost or demote by tag. Example: boost verified chunks 1.5×, demote internal-draft chunks 0.5×.

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Source boost

Boost specific documents or collections. Useful when you have a canonical source you want to prefer over crawled copies.

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Reranker

Optional cross-encoder pass over the top ~20 fused results. It re-scores each (query, chunk) pair with a small transformer that reads both together — much more accurate than embedding cosine similarity alone.
  • Adds 150-300ms latency.
  • Adds a small per-query cost.
  • Meaningfully improves recall@1 on hard queries.
Turn on in your Retrieval preset. Also configurable: rerank top K (how many candidates to rerank, default 20) and model (choose from available cross-encoders).

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Diversity

Sometimes the top 6 chunks are all near-duplicates. Turn on Diversity to enforce some spread:
  • MMR (Maximum Marginal Relevance) — trades a little relevance for less redundancy. Set lambda (0=max diversity, 1=max relevance). Default 0.7.
  • Group cap — at most N chunks per source. Prevents one huge document from crowding out the top results.

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Score cutoff

Below-cutoff chunks are dropped even if they’re in the top K. Prevents the Agent from being handed a low-confidence match just to fill the K quota. Score is in RRF space, roughly 0-1. Default cutoff 0.15. Turn up for higher precision; turn down (or to 0) for higher recall.

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Query-time overrides

Any of the above can be overridden per-call. An Agent may set a higher cutoff when the domain is high-risk, or turn on the reranker only for questions containing “safety” or “compliance”.

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Watching it work

The Trace view shows the retrieval step with:
  • The final query used (after any rewriting).
  • Every candidate with its vector score, keyword score, fused score, and any boosts applied.
  • Whether the reranker changed the order.
If retrieval feels off, this is where you look first.