What is entity resolution at scale?

Matching messy strings—like 'AirPods Pro 2' vs full Amazon titles—to real products across sites. SmartReview does 5k/day at 94% accuracy.

How does SmartReview match products without ML?

Normalization (60%), fuzzy Levenshtein (brand exact, model 85%), external search validation. No neural nets needed.

Is entity resolution solved by AI now?

Not yet—LLMs promise it, but production reliability lags. SmartReview's rules beat hype for now.

🗄️ Databases & Backend

SmartReview Cracks Product Matching Across 50 Sites—No ML PhD Required

AirPods Pro 2. Apple AirPods Pro (2nd Generation). Same damn earbuds, different names everywhere. SmartReview nails entity resolution at scale without the ML circus.

theAIcatchup Apr 10, 2026 3 min read

SmartReview entity resolution pipeline matching AirPods across Amazon, Reddit, RTINGS

⚡ Key Takeaways

Normalize ruthlessly: brands exact, generations regex, 60% wins. 𝕏
Fuzzy matching with category guards prevents disasters like over-ear/in-ear mixups. 𝕏
External validation scales accuracy but risks API dependency—watch costs. 𝕏

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theAIcatchup

Ship faster. Build smarter.

#data-engineering #entity-resolution #fuzzy matching #product matching

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