OVERVIEW · 01 / 06
AI Property Condition Grading Tool
Photos in, a graded condition report out, and a condition-adjusted property value that your table controls, not the AI.
Prepared for Russ · Rough estimate for a stable solution, indicative only. Exact quote and development plan to follow once the open points from our thread are settled.
INVESTMENT · 02 / 06
$8,000 – $9,000
1 – 1.5 months
Rough estimate for a stable solution: grading that stays consistent, an admin console you control, and the capacity for the daily volume we discussed.
You don't wait until the end to show it
Around the middle of the build the tool already works end to end. You can put it in front of real users and start collecting leads from it while we keep tuning the grading and hardening it for volume in parallel. One build, one price. You just start getting value out of it before it is finished.
WHAT GETS BUILT · 03 / 06
The user enters the address and the system retrieves the starting valuation to work from, with a manual override so a value can also be entered or passed in directly. This integration is inside the estimate. The open question is which data source it reads from, and that is a commercial decision as much as a technical one.
Eleven components each get their own upload slot, and the user marks N/A for anything the property doesn't have. Photos are validated, resized and stored before any grading runs. Slot-based upload means missing coverage is visible up front instead of surfacing as UNKNOWN at the end of the report.
Each component is graded from its photos and returned with a confidence score and a one-line reason citing what was actually visible. The model describes only what it can see, never infers hidden defects, and never touches a dollar figure.
The percentage matrix lives in the database, not in the code and not in the prompt. The grade comes from the AI, the percentage comes from your table, the calculator multiplies. Change a percentage and every report from that point forward changes with it.
The user sees the starting value, the overall condition, the total adjustment and the condition-adjusted estimate, with a component-by-component breakdown showing exactly how the number was reached. Nothing in the report is unexplainable.
We run the grader against your labelled photo set, compare every grade to yours, adjust the instructions and run it again, until the same kitchen gets the same grade twice. This is the difference between a demo that grades one photo impressively and a tool that stays consistent across a hundred strangers a day.
Edit the percentage matrix, the grading instructions for each component, the minimum confidence threshold, which components are active, and the maximum total adjustment. No developer and no deploy. Every change is versioned so a bad edit can be rolled back.
Each report stores the model version and the exact rule set used to generate it. Six months from now, after the percentages have moved twice, you can still reproduce any number a seller was shown and explain where it came from.
When confidence falls below your threshold the component returns UNKNOWN with a specific request for better photos, and the value is left untouched rather than estimated. The user can add the missing photos and re-grade without starting the whole thing over.
Queueing, retries, rate limiting and per-request cost controls, so the tool keeps its response times at the daily volume we talked about and you never meet a surprise bill or a stalled queue.
HOW IT WORKS · 04 / 06
The grader, running on your own example
Change any grade and watch the value move. The grades come from the AI. The percentages come from your table.
Roof
Shingles uniform, no visible damage or sagging.
Confidence 0.90
Kitchen
Older cabinetry, dated countertops and appliances, with visible wear.
Confidence 0.92
Bathrooms
Functional and clean, but dated vanity and tilework.
Confidence 0.81
Flooring
Mixed flooring types, visible damage in two rooms.
Confidence 0.88
Exterior / Paint
Paint fading on the south elevation, siding intact.
Confidence 0.76
Windows
Double-glazed units, frames in good order.
Confidence 0.85
Doors
Front and interior doors recently replaced.
Confidence 0.83
Landscaping
Overgrown beds, damaged fencing along the rear line.
Confidence 0.87
Garage
Structurally sound, door mechanism visibly aged.
Confidence 0.79
Laundry Room
Modern hookups, clean surfaces, no visible wear.
Confidence 0.84
Deck / Patio
No deck or patio on this property.
Confidence —
Maximum this matrix can express: -17.25% ($413,750). Worth a conversation about how it should behave on a property a bank won't lend against.
Sample data, for illustration.
COST DRIVERS · 05 / 06
Which data source the valuation comes from
The integration itself is included in this estimate. What is still open is where the number actually comes from. Zillow's own terms are restrictive at the daily volumes you described, and a licensed valuation provider is cleaner but carries its own monthly data cost. That choice moves the estimate at the edges, and it is worth deciding together rather than by default.
The photo set you give us
This is the part that quietly decides the timeline. A set of real properties carrying your own grades gives us something to tune against and measure against. Without one we are guessing at your standard and calling it accuracy, and the tuning takes considerably longer.
The front end you have already built
We have not seen it yet. If the pages are wired and ready to connect, the integration is quick. If they are closer to a design than a working app, there is more to do on that side, and that is the single biggest unknown left in this number.
Not on this list: the confidence threshold. That one is a setting rather than a build, so it barely moves the estimate. Worth deciding early anyway, because it changes how the tool feels to use.
One architectural note
We would store the percentage matrix and the grading instructions as versioned records from the first day, and stamp every report with the versions that produced it. It costs almost nothing now and is close to impossible to add later, because the moment you retune the percentages every report you have already shown a seller becomes unexplainable. It is also exactly what version two needs on the day repair-cost line items arrive.
NEXT STEP · 06 / 06
Your reply moves this forward
If this range fits what you had in mind, tell me and I will turn it into an exact quote with a development plan, a sequence and the milestones. If it does not fit, tell me where you need it to land and I will be straight with you about what would have to come out to get there.
The open points from my last message still stand, and the photo set is the one I would start on today regardless of what you decide about the rest.
Reply in our chat.
Temy · Vadym