PropTech · Agentic AI · Mobile App

An agentic AI property search that shows what it understood

Scout is a conversational way to find a home to rent in Dubai, explored for Property Finder. You say what you want in your own words. Scout keeps a short memory of what it understood, marks what it guessed, and shows only the homes that match. It runs on a real model. Nothing is mocked.

Role
Designer and builder
Built with
Claude Code, Claude API
Time
A few hours
Year
2026
Try the prototype (opens in a new tab)Best on a phone

A prototype, made as a design exploration. Not affiliated with or endorsed by Property Finder.

  1. You: 2-bed near my office in DIFC, around 130k a year. I have a dog
  2. Scout: DIFC itself has nothing at 2-bed near 130k. Closest is Business Bay, one minute's drive away: a pet-friendly 2-bed at Executive Towers, 138k, 640m from the metro. Does 138k work, or should I keep the budget closer to 130k?
  3. You: Actually I can go to 150k if there's a pool
  4. Scout: With 150k as the ceiling and a pool required, that Executive Towers 2-bed at 138k still fits, pool included.
  5. You: Just for now, show me anything under 110k
  6. Scout: Under 110k, nothing near DIFC has a pet-friendly 2-bed with a pool. Drop the area and there are 5 options elsewhere, starting at 72k in Town Square. Want me to widen the search beyond DIFC's area?
  7. You: Being near DIFC isn't important, drop it
  8. Scout: Dropping the DIFC pin opens up five pet-friendly 2-beds under 110k, all with pools. Town Square starts lowest at 72k, then JVC at 88k, Mirdif at 92k, Al Barsha at 95k, and Motor City at 105k.

The challenge

In a filter panel, your intent is on screen. In a chat, it scrolls away.

Search with filters is easy to read. What you asked for sits in one place, you set every part of it, and the results are clearly built from it.

A chat loses that. What you want is spread across messages: some said, some implied, some changed three messages later. And you can’t see what the results are based on.

The challenge: keep a memory of what you asked for, easy to change and clear about what the results are based on, without a filter panel.

The design

One loop, and a memory you can see.

Two rules hold it together

Nothing changes silently.

What you see in the memory is exactly what the results were built from.

01

See it. Always in view, never in a panel.

Filters do one thing well: they’re always there. I kept that and dropped the panel. One line above the keyboard, in thumb reach, written in words instead of controls.

No quick-reply chips either. Chips are filters by another name.

02

It infers, and shows its working.

An agent that only does what it’s told is a form. Scout reads between the lines: a dog means a pet-friendly building, kids mean schools nearby probably matter.

What must be true filters. What’s only likely ranks. Every guess is marked as one.

03

Correct it. Tap a phrase, or just say it.

The memory opens as a sentence you can disagree with, phrase by phrase. Taps and words both go through the conversation, so the memory and the chat never disagree.

04

Steer it. Change course without losing your place.

“Just for now” sits on top of what you said before and never replaces it. Drop it, and you’re back where you were.

05

No results is never the answer.

Saying “no results” is easy. A smart agent works out why, and what would change it.

Scout first widens to what you’d likely accept anyway: the neighbouring areas. If still nothing fits, code tests every requirement, finds the one blocking the most homes, and Scout names it with what you’d get. It never drops a requirement without asking. You decide what to give up.

How the agent works

The model reads people. Code does the counting.

Understanding a person is fuzzy work. Matching homes is exact: a budget is a number, and a building either allows pets or it doesn’t. So each half goes to what does it best. The memory on screen is where they meet.

The memory on screen is the single source of truth. Results are built from it and nothing else, and every change to it is said out loud once.

Technical choices for this prototype

2Models, each chosen for its job: a fast one to understand, a stronger one to write.
46Seeded homes across 20 Dubai communities, shaped to test the edges of the conversation.
~6sSaved on every turn by asking for plain JSON first, with strict schema mode as the fallback.

Building it

Built with Claude Code, end to end, in a few hours.

I decided what Scout should do, how it should talk, and where the model stops and code takes over. Claude Code wrote the interface, the prompts, the matching code and the tests. I judged every answer.

The prompts are design work. Scout’s voice lives in the reply prompt: short sentences, plain international English for a city of expats, no idioms, always the area, the price and the distance.

The test it has to pass

A script replays a seven-turn conversation against the live model. It fails if Scout…

  • uses an em dash
  • uses an idiom or filler, like “good news”
  • asks a question while homes are on screen
  • opens two replies the same way
  • forgets a preference you never took back
  • shows a home over a firm budget
  • shows a no-pets home after you mention a cat or dog
  • reads “10k a month” as anything but 120k a year

Try it. It’s a real model on seeded homes.

Open Scout (opens in a new tab)Best on a phone. A demo session allows 15 messages.

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