DUAL MLS A.I.

Revolutionizing The Real Estate Industry

Price Prediction

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What goes into a price prediction Learn the process

How it Works
The AI-powered Price Prediction Tool enhances property valuation accuracy by integrating advanced CMA data and MLS inputs. It calculates precise price per square foot using comparable sales from nearby properties, adjusting predictions based on updates, geographical factors, and market trends. By gathering detailed data, such as sale prices and square footage from similar homes, the AI predicts the target property’s value with increased precision. For example, a target property of 2,310 sq ft may have an estimated value of $161,738 at an average price of $70 per square foot, with adjustments for recent updates and market conditions.

In short

Key Features of the AI-Driven Price Prediction

The AI-powered Price Prediction Tool enhances accuracy by integrating CMA data, calculating precise price per square foot from comparable properties, and adjusting predictions based on MLS data, property updates, and geographical factors.

In short

Price Prediction Process

The AI-powered price prediction tool retrieves sale prices and square footage from five comparable properties to calculate a precise price per square foot, adjusts for property updates and market trends, and predicts the target property’s value with accuracy, offering realtors a reliable and efficient valuation method.

How it works? DEEP DIVE !

Advanced CMA Integration

Enhanced Accuracy: The tool uses the same data inputs as a traditional Comparative Market Analysis (CMA) but applies AI-driven calculations to increase precision.

Comprehensive Data: Pulls sale prices from comparable properties in the neighborhood to inform its predictions.

Accurate Price Per Square Foot

Precision Calculations: Based on the total square footage of comparable properties, the AI calculates a highly accurate price per square foot, offering a more reliable basis for valuation.

MLS Data Integration

Property-Specific Information: AI collects detailed property data from MLS, including images, historical information, and when the house was built.

Update-Based Adjustments: The AI assesses whether the property has been updated in the last 5 or 10 years. Depending on the quality and recency of the updates, the AI either increases or decreases the predicted value.

Geographical and Location-Based Factors:

Location-Specific Adjustments: The AI takes into account the geographical location, including specific factors from Perk County and other areas, to fine-tune its price predictions.

Color-Coded Results: Comparable's with a likeness of over 80% are highlighted with a green box, while those with lower similarity (below 80%) are displayed in yellow, making it easy to identify the most relevant comps.

Gather Sale Prices of Comparable Houses

AI retrieves sale prices from five comparable properties within the same or nearby neighborhoods to inform the price prediction.

Example:
House 1: $167,876 (Same neighborhood)
House 2: $160,893 (Same neighborhood)
House 3: $164,786 (0.25 miles away)
House 4: $165,089 (0.75 miles away)
House 5: $156,490 (1 mile away)
Total Sale Price: $815,134

Calculate Total Square Footage

The total square footage of these five properties is summed to provide a basis for the price per square foot calculation.

Example:
House 1: 2,300 sq ft
House 2: 2,234 sq ft
House 3: 2,464 sq ft
House 4: 2,346 sq ft
House 5: 2,298 sq ft
Total Square Footage: 11,642 sq ft

Determine Price Per Square Foot

Divide the total sale price by the total square footage.

Example: $815,134 / 11,642 sq ft ≈ $70.02 per sq ft

Predict the Price of the Target Property

Multiply the target property’s square footage by the calculated price per square foot to predict its value.

Example: If the target property is 2,310 sq ft, the predicted price is approximately $161,738.

Additional Adjustments

Property Updates: AI analyzes the first eight property pictures to determine whether any recent updates or renovations were made. If updates are detected, the predicted price is increased by 10%.

Market Trends: The AI adjusts the price based on monthly market trends provided by MLS, reflecting market conditions within the property’s county, adding or subtracting value as necessary.
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Behind the Dual A.I. Price Prediction

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Road Map

Phase 1

September 9th 2024

Listing Description and Sound Like Me

AI generates accurate listing descriptions by utilizing comprehensive MLS data, geolocating the address to incorporate nearby features, and analyzing MLS images. This integration of MLS data, geographical context, and property images results in a thorough and detailed property description.

September 9th 2024

White Label Feature

Full white labeling of the AI for the MLS and Real Estate Agents, allowing customization of the domain, logo, and feature descriptions.

November 18th 2024

Property Comparison (CMA)

When a property is searched, the AI will prompt realtors to confirm or correct bed, bath, and square footage details before proceeding with the comparison process. A ranking system based on percentage match will help realtors assess the similarity of comparables to the subject property, with specifics outlined in the project specifications.

November 18th 2024

Shareable Live Link

Allows realtors to personalize the property comparison page for client presentations in PDF or link formats, with options for adding their name, brokerage logo, preferred colors. These customizations will only affect the viewer’s perspective and not the general settings.

November 18th 2014

Price Prediction

finds comparables to calculate the price per square foot and estimated price of the subject property, integrating MLS market trend data into the A.I analysis. Property images will be analyzed to determine updates, and the predicted price will be adjusted based on a predetermined value system that adds or subtracts a percentage of the square footage.

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Phase 2

June 2025

Automated Social Media Posting

Agents can upload videos to be professionally edited and shared on social media. If no content is provided, the AI will gather information and images from the MLS and Google to generate and publish posts on social media platforms.

June 2025

Automated Home Buying Process (Follow up CRM)

This feature simplifies realtors’ tasks by automating home search and client communication. Realtors can input client preferences, and the AI scrapes listings based on those details, allowing them to either send listings directly to clients or receive them first. The AI can interact with clients, setting up showings and booking appointments in the realtor’s calendar, while providing status updates and summaries via text. Realtors can manage client information, adjust search criteria, and track client activity through an easy-to-use interface that supports efficient workflow.

June 2025

Tax Appeal Letter Generation

drafting property tax appeal letters by automating the process through public data analysis, comparable property searches, and legal letter generation, with a user-friendly interface and ongoing support.

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Phase 3

November 2025

Automated Contracts + Bullet Point Review

Agents will be able to get contracts filled out by answering a field of questions and then the A.I. will generate bullet points going over the most important parts 

November 2025

Broker Bot

Agents will be able to ask the A.I. questions and have a conversation about broker laws and regulations that are up to date with current information 

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Contact Us

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