jakeCarsAI

Jake’s Cars AI - Automotive Dealership Intelligence System

Project Overview

AI-powered automotive dealership management system that optimizes customer-lender-vehicle matching, replacing manual processes with intelligent automation.

Client: Scott Auto Dealership (Jake - JMU)
Developer: Mindgrub AI Solutions
Timeline: 31 days (3 phases)
Investment: $45,000 - $70,000
ROI Target: $140,000 annual savings

Quick Links

Meeting Notes - Detailed client requirements and system analysis
Structure of Work - Contract, phases, and deliverables
Project Documentation - All project planning documents

Current Status

🚀 Phase 1 - MVP Internal Tool (10 days)

Database architecture and migration from Google Sheets
AI-powered customer profiling and lender matching
Real-time payment calculator and inventory optimization
Web application with MCP server architecture

System Architecture

Core Features

Smart Customer Profiler: AI data extraction/validation
Intelligent Lender Matching: 30+ lender optimization engine
Dynamic Payment Calculator: Real-time scenario generation
Inventory Optimizer: AI vehicle recommendations
Sales Assistant Agent: Natural language interface

Technology Stack

Frontend: Next.js 14 with Tailwind CSS
Backend: Node.js with Prisma ORM + PostgreSQL
Schema Validation: Custom type-safe validation system
AI: Multi-agent system using models
Real-time: WebSocket connections
MCP Architecture: Remote MCP servers with packaged prompts, tools, and resources

API Integrations

Auto Database API: Vehicle inventory and pricing data
Route One API: Lender portal integration
Credit Bureau API: Credit report services
Vehicle Valuation API: Trade-in value services
Dealer Management System: Integration with existing DMS

Development Phases

Phase 1: MVP Internal Tool (10 days)

Goal: Production-ready internal system replacing Google Sheets

Database migration and optimization
Core AI features implementation
Web application development
MCP server architecture setup

Phase 2: Advanced AI Features (7 days)

Goal: Enhanced automation and intelligence

Advanced API integrations
Multi-agent workflows
Analytics and reporting dashboard
Predictive modeling

Phase 3: Commercial MCP Product (14 days)

Goal: Market-ready SaaS solution

Multi-tenant architecture
White-label capabilities
Go-to-market assets
Commercial deployment

Getting Started

Prerequisites

Node.js 18+
PostgreSQL 15+
Git
Docker (optional)

Installation

# Clone repository
git clone https://github.com/w4ester/jakeCarsAI.git
cd jakeCarsAI

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env

# Set up database
npm run db:setup

# Start development server
npm run dev

Project Structure

jakeCarsAI/
├── src/
│   ├── components/        # React components
│   ├── pages/            # Next.js pages
│   ├── api/              # API routes
│   ├── lib/              # Utility functions
│   ├── types/            # TypeScript types
│   └── mcp/              # MCP server components
├── prisma/               # Database schema
├── public/               # Static assets
├── docs/                 # Documentation
└── tests/                # Test files

Business Impact

Current Pain Points

40% of sales team time spent on manual quote generation
Complex synthesis of 30+ lender requirements
Difficulty finding optimal customer-vehicle-lender matches
Google Sheets scalability limitations

Expected Benefits

50% reduction in quote generation time
$140,000 annual savings (2 FTE equivalent)
Improved customer satisfaction
Scalable architecture for growth

Contact Information

Project Lead: Will - Mindgrub AI Solutions
Client: Jake - Scott Auto Dealership
Repository: https://github.com/w4ester/jakeCarsAI.git

This project is built with FIRST_PROGRAMMING_PRINCIPLES and modern AI architecture for maximum efficiency and scalability.