EstateAI

EstateAI is an AI-driven platform that tells you whether a property is a good investment backed by cash flow, risk analysis, and clear explanations so you can invest with confidence.

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Inspiration

Real estate investing has traditionally been gated behind access to capital, insider knowledge, and time-consuming analysis. While platforms like Zillow or Redfin surface listings, they rarely answer the real question investors care about: Is this actually a good deal?

For students, first-time investors, and small-scale landlords, underwriting a property often requires spreadsheets, calculators, and experience they lack. Many promising opportunities are missed simply because the analysis barrier is too high. We wanted to build a tool that democratizes real estate deal analysis, allowing anyone to evaluate a property in minutes rather than hours.

What it does

Summary: Our web app allows users to select a property directly from an interactive map and instantly receive an AI-driven investment analysis. The system simulates how different investor profiles would evaluate the deal, calculates key financial metrics, and produces a clear Buy / Watch / Avoid recommendation with transparent reasoning.

Instead of overwhelming users with raw numbers, we translate data into actionable insights.

Key Features

Interactive Map-Based Property Selection

Users can click on properties directly from a map interface to analyze them in context. This removes friction from manual data entry and keeps the experience intuitive.

AI-Driven Deal Analysis Engine

We generate multiple specialized agents that simulate how different investor personas (cash-flow focused, appreciation focused, conservative, aggressive) would evaluate the same property using the same inputs.

Data-Driven Investment Dashboard

Each property is broken down into clear visuals and metrics, including:

  • Monthly cash flow
  • Cap rate
  • Cash-on-cash return
  • Operating expenses
  • Mortgage estimates
  • Risk indicators

Metrics That Matter

We focus on the numbers that actually drive real estate decisions:

  • Net Operating Income (NOI)
  • Cash flow after financing
  • Cap rate
  • Long-term ROI projections

We intentionally avoid vanity metrics and prioritize decision-grade financials.

How we built it

Frontend

  • TypeScript
  • React
  • Tailwind CSS
  • OpenStreetMap

Backend -FastAPI -MongoDB -A2A backend using Fetch.AI -Python -Hosted on Vercel

Challenges we ran into

Challenge 1: Inconsistent Property Data

Real estate data varies widely in completeness and reliability. We had to build normalization and validation logic to ensure the analysis engine remained stable even when some inputs were missing or noisy.

Challenge 2: Designing Meaningful AI Outputs

Rather than letting AI generate generic advice, we spent significant time engineering prompts and agent roles so each response was grounded in real financial logic and traceable assumptions.

Challenge 3: Backend–Frontend Synchronization

Maintaining a smooth, real-time experience between map interactions and backend analysis required careful API design and state management to keep results fast and responsive.

Accomplishments that we're proud of

We successfully built a full investment decision pipeline that transforms a simple map click into a detailed financial analysis. Our agent-based approach produces explanations that are not only informative but also easy for beginners to understand. The frontend and backend integrate seamlessly, and the UI delivers complex insights without overwhelming the user.

What we learned

  • AI as a decision support tool: AI is most powerful when structured around clear rules and financial logic.

  • Data abstraction: Translating raw property data into meaningful investment signals is more valuable than adding more data.

  • UX matters: Investors need clarity and confidence, not spreadsheets.

  • Iterative development: Rapid testing and refinement were key to building a reliable analysis engine under time constraints.

    What's next for Estate.AI

    We plan to expand the platform with:

  • Rental market trend analysis

  • Portfolio-level insights

  • User-defined investment strategies

  • Support for additional asset types (multi-family, commercial)

Long-term, we aim to build a personal investment copilot that helps users grow from first-time buyers into confident, data-driven investors.

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