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ann-precision: inline the four-layer framework and MTEB ceiling note

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Replaces the external pointer to retrieval-quality-fundamentals with a
self-contained section introducing the four evaluation layers. The tutorial
no longer depends on fundamentals for orientation.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Dylan Couzon
2026-04-23 23:15:34 -04:00
co-authored by Claude Opus 4.7
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commit 29640488d9
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qdrant-landing/content/documentation/tutorials-search-engineering/retrieval-quality.md
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This tutorial focuses on **ANN precision**: how closely approximate nearest-neighbor (ANN) search matches exact kNN search.
To measure ANN precision, you compare Qdrant's approximate top-k against the exact kNN top-k using `precision@k`, then tune HNSW parameters to trade memory and build time for higher precision.
To learn more about retrieval quality evaluation, see the <a href="/documentation/tutorials-search-engineering/retrieval-quality-fundamentals/#the-evaluation-ladder" target="_blank">evaluation ladder</a>.
## The Four Layers of Retrieval Evaluation
Retrieval quality operates at four layers. Each catches different failure modes at a different cadence and cost. This tutorial covers layer 1.
- **Layer 1: ANN precision** (this tutorial). How closely approximate nearest-neighbor search matches exact kNN. Run on every index or embedding change.
- **Layer 2: Retrieval relevance** ([Building a Golden Query Set](/documentation/tutorials-search-engineering/retrieval-quality-golden-set/)). How well the results match query intent against a labeled dataset. Run weekly, or on retrieval-stack changes.
- **Layer 3: Pipeline output quality** ([Evaluating Pipeline Output Quality](/documentation/tutorials-search-engineering/retrieval-quality-pipeline-output/)). Whether the full pipeline (retrieval plus an LLM generator, a ranker, or a UI) produces the right output. Run weekly, or on retrieval or generator changes.
- **Layer 4: Business impact**. Whether better retrieval moves the KPIs the business cares about. Measured per release once the offline layers pass.
Retrieval quality sits on top of embedding quality. Embedding quality is measured separately by benchmarks like [MTEB](https://huggingface.co/spaces/mteb/leaderboard) and sets the ceiling on every downstream metric.
## Measure ANN Precision with the Web UI