🚀 AI Spend Audit | B2B SaaS MVP

Stop bleeding money on redundant AI subscriptions. A financial audit engine for modern engineering teams.

📋 Table of Contents

• The Problem
• The Solution
• Key Features
• Strategic Documentation
• Tech Stack
• Getting Started
• Roadmap

🚨 The Problem

Modern engineering teams are unknowingly stacking overlapping AI tools. A single team might pay for Cursor (Pro), GitHub Copilot, ChatGPT Plus, and Claude Pro simultaneously.

• Feature Overlap: Paying for features that are already bundled in other tools.
• Wasted Seats: Premium individual licenses assigned to light-users.
• Manual Nightmare: Engineering Managers lack the time to manually audit and optimize these recurring costs via spreadsheets.

💡 The Solution

An automated, frictionless AI Spend Audit Engine. Users input their team size and current AI stack. Our engine calculates the exact financial waste, identifies redundancies, and provides a clear, actionable path to downgrade or consolidate—saving companies thousands of dollars annually.

✨ Key Features

• ⚡ Automated Financial Engine: Instantly calculates monthly/annual savings based on real-time SaaS pricing.
• 🔍 Redundancy Detection: Flags overlapping tools (e.g., paying for Copilot when already using Cursor).
• 💼 Licensing Optimization: Recommends API-based workspaces or Team plans over expensive individual seats.
• 🔒 Privacy-First Lead Capture: Shows the exact $ savings before asking for an email, ensuring high-intent lead generation and building trust.

📂 Strategic Documentation (Business Logic)

This repository is not just a technical MVP; it contains fully fleshed-out, market-validated business logic. Please review our core documents to understand the strategy behind the code:

1. User Interviews & Market Validation - Deep psychological insights, friction points, and product pivots based on 3 real developer interviews.
2. Go-To-Market (GTM) Strategy - Zero-budget, founder-led acquisition channels.
3. Unit Economics & Pricing - Value-based monetization and CAC/LTV projections.
4. Core Metrics - Our North Star metric and secondary growth levers.
5. Landing Page Copy - High-converting, outcome-focused marketing text.

🛠️ Tech Stack

• Frontend: HTML5, CSS3, Vanilla JavaScript (Built for absolute speed and zero dependencies)
• Architecture: Client-side calculation engine
• Version Control: Git & GitHub

🚀 Getting Started (Run Locally)

1. Clone this repository:

   git clone https://github.com/ravithakur776/AI-Spend-Audit.git