Skip to content

AppArt Agent

AI-powered apartment purchasing decision platform for France

AppArt Agent helps buyers make informed real estate decisions by combining French property transaction data (DVF) with AI-powered document analysis and visualization tools.

Features at a Glance

flowchart LR
    subgraph Input["Your Input"]
        Address["Property Address"]
        Docs["Documents<br/>(PV AG, Diagnostics,<br/>Tax, Charges, Other)"]
        Photos["Apartment Photos"]
    end

    subgraph AI["AI Analysis"]
        DVF["Price Analysis<br/>5.4M+ transactions"]
        DocAI["Document Analysis<br/>Native PDF + Thinking"]
        PhotoAI["Photo Redesign<br/>Style visualization"]
    end

    subgraph Output["Decision Support"]
        Price["Market Valuation"]
        Risks["Risk Assessment<br/>+ Confidence Score"]
        Costs["Cost Breakdown<br/>+ Tantiemes"]
        Visual["Renovation Preview<br/>+ Promoted Redesigns"]
    end

    Address --> DVF --> Price
    Docs --> DocAI --> Risks
    Docs --> DocAI --> Costs
    Photos --> PhotoAI --> Visual

Price Analysis

Access 5.4M+ French property transactions from DVF data to understand market prices, trends, and get personalized recommendations.

Learn more →

Document Analysis

Upload PV d'AG, diagnostics, tax documents, charges, and other property documents (rules, contracts, insurance). AI automatically classifies, analyzes with native PDF processing and reasoning, and produces a cross-document synthesis with cost breakdowns, tantiemes calculation, risk factors, and buyer action items.

Learn more →

Photo Redesign

Visualize renovation potential with AI-powered style transformation of apartment photos. Promote your favorite redesign to feature it on the property overview.

Learn more →

Decision Dashboard

Property overview with AI synthesis summary, risk level badges, annual/one-time cost breakdowns, promoted redesign previews, and inline property editing.

Learn more →

Quick Start

# Clone and setup
git clone https://github.com/benjamin-karaoglan/appart-agent.git
cd appart-agent
cp .env.example .env
# Configure AI: set GEMINI_USE_VERTEXAI=true or add GOOGLE_CLOUD_API_KEY

# Start services (migrations run automatically)
docker-compose up -d

# Access
# Frontend: http://localhost:3000
# API Docs: http://localhost:8000/docs

Full installation guide →

Architecture Overview

flowchart TB
    subgraph Client["Client Browser"]
        Browser["Web Browser"]
    end

    subgraph Frontend["Frontend - Next.js 14"]
        Dashboard["Dashboard<br/>+ Synthesis Preview"]
        Documents["Documents<br/>+ Multi-phase Processing"]
        Properties["Property Detail<br/>+ Inline Editing"]
        Photos["Photo Studio<br/>+ Promoted Redesigns"]
    end

    subgraph Backend["Backend - FastAPI"]
        API["REST API"]
        AIServices["AI Services<br/>Native PDF + Thinking"]
        DocProcessing["Document Processing<br/>+ Cross-doc Synthesis"]
    end

    subgraph DataLayer["Data Layer"]
        PostgreSQL[("PostgreSQL<br/>5.4M+ DVF")]
        Redis[("Redis Cache")]
        Storage[("MinIO / GCS")]
    end

    subgraph External["External Services"]
        Gemini["Google Gemini<br/>Vertex AI"]
    end

    Browser --> Frontend
    Frontend --> Backend
    API --> PostgreSQL
    AIServices --> Redis
    DocProcessing --> Storage
    AIServices --> Gemini
    Properties --> API

Architecture details →

Deployment Options

flowchart LR
    subgraph Local["Local Development"]
        Docker["Docker Compose<br/>Free, all-in-one"]
    end

    subgraph Cloud["Production"]
        GCP["GCP Cloud Run<br/>~$65-445/month"]
    end

    Local -->|"Ready for prod?"| Cloud
Environment Best For Guide
Docker Compose Development, testing Docker Guide
GCP Cloud Run Production, scaling GCP Guide

Technology Stack

Layer Technologies
Frontend Next.js 14, React 18, TypeScript, Tailwind CSS, Better Auth, next-intl, pnpm
Backend FastAPI, Python 3.10+, SQLAlchemy, UV
Auth Better Auth (email/password + Google OAuth), HTTP-only session cookies
AI/ML Google Gemini 2.0, Vertex AI, LangChain
Database PostgreSQL 15, Redis 7
Storage MinIO (local), Google Cloud Storage (production)
Infrastructure Docker, Terraform, GCP Cloud Run

Documentation Sections

flowchart TB
    Start["Getting Started"]
    Arch["Architecture"]
    Backend["Backend"]
    Frontend["Frontend"]
    Deploy["Deployment"]
    Dev["Development"]

    Start --> Arch
    Arch --> Backend
    Arch --> Frontend
    Backend --> Deploy
    Frontend --> Deploy
    Deploy --> Dev

Support