Vol. 01 · № 24A technical journal on AI searchUpdated Sep 25, 2026
Recall Monitor
How answer engines decide which brands to name, measured. Research from our own runs, field guides, and notes on the tools and plumbing underneath.
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- Vector databasePinecone88%[69–96] n=24/
- Vector databaseQdrant88%[69–96] n=24/
- Vector databaseWeaviate83%[64–93] n=24/
- Vector databaseMilvus83%[64–93] n=24/
- Vector databaseElasticsearch21%[9–40] n=24/
- Vector databaseChroma17%[7–36] n=24/
- Vector databasepgvector0%[0–14] n=24/
- Vector databaseRedis0%[0–14] n=24/
- Decentralised exchangeUniswap67%[52–79] n=42/
- Decentralised exchange1inch52%[38–67] n=42/
- Decentralised exchangeJupiter36%[23–51] n=42/
- Decentralised exchangeCurve29%[17–44] n=42/
- Decentralised exchangeOrca24%[13–39] n=42/
- Decentralised exchangeRaydium21%[12–36] n=42/
- Decentralised exchangeAerodrome14%[7–28] n=42/
- Decentralised exchangePancakeSwap12%[5–25] n=42/
Research
Measurements, studies and what the data says about how answer engines choose.