Open House Feedback Summarizer

Paste open house feedback and an AI model in your browser groups likes, concerns, price comments and follow-ups.

Free, private, no signup.

Last updatedHow we build & check our tools

Interactive Tool

This tool runs in your browser and is loading now.

Enter your values once it appears to see your results.

How Open House Feedback Summarizer works

Press Load model once: your browser downloads Gemma 3 1B instruction-tuned (web build) (728 MB) from this site and keeps it in its cache. Then add your text and press Summarize locally. The model runs on this device using your graphics card, so nothing you enter is sent to a server. Until the model is loaded, or if your device cannot run it, the tool falls back to a simple keyword check and labels the result as the fallback.

Gemma 3 1B instruction-tuned (web build) is a small open language model from Google. The tool sends it the instruction below plus your text, asks for a JSON answer with fixed fields, and shows each field as a card. It runs at temperature 0, so the same input gives the same answer on the same device, though different graphics cards can word it slightly differently.

Inputs longer than 6,000 characters are cut to that length before they reach the model, and the result says so. The model only sees what you paste: it does not look anything up.

The instruction also carries one worked example: the built-in sample with the answer the larger Gemma 4 E2B model gave for it. That example is what lets this smaller model follow the answer format reliably.

The instruction the model gets

You summarise visitor feedback from an open house for the listing agent and seller. Group what people liked, their concerns, and comments about price, and call out themes that more than one visitor raised, keeping any counts exactly as written in the notes. Use the visitors' wording. Do not recommend a price change or compute anything from the numbers, and do not invent feedback that is not in the notes. Do not do any arithmetic: copy prices, dates, ages and amounts exactly as written, and never compute totals, differences or percentages.

What it returns

  • What visitors liked: Positive comments, in their words.
  • Concerns: Negative comments and objections, in their words.
  • Price comments: What visitors said about the price, with any figures as written, or empty if nothing.
  • Repeated themes: Points raised by more than one visitor, with the count as written if given.
  • Follow-up actions: Two or three things the agent could clarify or prepare for the next showing (for example roof age documents).

Worked example

The model's output for the built-in sample, recorded on a desktop browser. Your run may word things slightly differently.

Feedback forms: loved kitchen and light, concern about highway noise, three buyers asked about roof age, two mentioned price feels high by $20k.
What visitors liked
loved kitchen loved light
Concerns
concern about highway noise
Price comments
two mentioned price feels high by $20k
Repeated themes
roof age
Follow-up actions
clarify roof age documents prepare for next showing

The model

The files are served from this site, versioned so a cached copy is never stale. Nothing is fetched from a third party while you use the tool.

You can switch models in the tool. Also available: Gemma 4 E2B instruction-tuned (web build) (2.0 GB). The larger language model gives more thorough answers but is a bigger download and needs a stronger device.

ModelDownloadRuns onLicence
Gemma 3 1B instruction-tuned (web build)700 MBGraphics card (WebGPU)Gemma Terms of Use
Gemma 4 E2B instruction-tuned (web build)2.0 GBGraphics card (WebGPU)Apache-2.0

Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms.

Limitations

  • Small language models make mistakes: they can miss an item, merge two, or state something more confidently than the text supports. Check the result against your input before you rely on it.
  • It needs WebGPU and about 4 GB of memory, so it is offered on desktops and laptops, not on phones and tablets. Devices that cannot run it get the keyword fallback, clearly labelled.
  • Results describe the input you gave, not the real-world situation behind it. Review them yourself before acting.
  • This is not financial, tax or legal advice. Confirm anything important against your own records and with a qualified professional.

Good uses

  • Turning a stack of open house cards into one seller-ready summary before the Monday call
  • Separating price objections from condition objections, which is the whole game
  • Spotting the fixable complaint (clutter, smell, listing photos) before you cut the price
  • Building a week-over-week record so you can show a seller the pattern, not just this week's mood

Frequently Asked Questions

Common questions about the Open House Feedback Summarizer

No. The model files download from this site once, and then everything runs in your browser tab. The text you enter is never sent to a server, and closing the tab discards it.

Sources & References

Mortgages and home-buying

Consumer guidance on mortgages, closing costs, and home financing.