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AI/MLProductSearch

Google Photos: Memory Search

Oct 2026

AI product case study on Google Photos. I analysed 705 public complaints, interviewed 6 users, and built and tested an AI prototype that finds half-remembered photos and says "no match" instead of guessing.

Google Photos: Memory Search

The problem

People often remember a photo only in pieces: a colour, a place, who was there. They can describe it, but Google Photos search often can't match that description to the photo. Search works on dates and faces, but not on descriptions.

What I found

- I collected 705 public complaints (Play Store, App Store, Reddit) and used an LLM to pick out 84 about retrieval.

- 59 of those 84 break at one stage: search can't read the clue the person gives.

- I interviewed 6 people. 3 of 6 described the photo clearly and still failed to find it.

What I built

An AI search prototype. Every photo has a plain-language caption plus its date, place and people. The typed memory and the captions go to an LLM, which returns the photos that fit, each with a 0–100 confidence score. If nothing is confident enough, it shows "no confident match" instead of guessing.

Results

I tested the prototype with 3 users from the same group. All 3 rated it above their own photo app (for example 4–4.5 out of 5 against 1 out of 5 for one tester). It never invented a match on a photo that wasn't there.

Links

Try the prototype: https://gp-retrieval-mvp.netlify.app/

Explore the complaint data: https://retrieval-radar.netlify.app/