FairPay — Compensation Intelligence & Negotiation Platform

FairPay is a compensation transparency and negotiation assistant built to eliminate information asymmetry in tech and professional compensation reviews.

It enables professionals to:

1. Compare compensation against role percentiles (median, average, top 10%).
2. Estimate role-adjusted target salaries with heuristic factor weighting (experience, education, location tiers, and skill profiles).
3. Generate customized negotiation strategies and emails powered by Gemini LLMs.
4. Analyze cross-industry pay distributions and gender wage parity trends through interactive visualizations.

• Percentile Calculation: Calculates exact percentile rank for your compensation against role-specific benchmarks.
• Statistical Breakdown: Computes average, median, and 90th percentile bounds.
• Actionable Verdict: Immediate feedback on whether your pay is at, above, or below prevailing market medians.

• Role-Adjusted Estimation: Calculates baseline targets adjusted by:
  • Tenure Multiplier: +5% compound per year of relevant experience.
  • Location Tiers: Adjusts for tech hub costs of living (Bangalore, Mumbai, Delhi NCR, Hyderabad, Pune).
  • Education Level: High School, Bachelor's, Master's, and PhD adjustments.
  • Skills Weighting: +2% per verified high-demand skill.
• Career Scenario Simulator: Interactive projections for acquiring new skills, relocating to tier-1 tech hubs, or transitioning to leadership.

• Tactical Strategy Playbook: Generates 5 high-leverage negotiation tactics tailored to your current vs. target salary gap and experience level.
• Formal Email Drafting: Drafts polished compensation review requests formatted for managers and HR.
• Built-in Fallbacks: Resilient design that provides structured heuristic playbooks even when external API limits are reached.

• Industry & Experience Distribution: Visual breakdowns using Recharts.
• Gender Pay Gap Analysis: Transparent reporting of percentage parity gaps across role categories.
• Anonymous Contribution: In-session entry simulation for community benchmarking.

• Frontend: React 19, TypeScript 5, Tailwind CSS
• Routing: React Router 7
• Visualization: Recharts
• AI Integration: Google Gemini API (gemini-1.5-flash)
• Build Tool: Vite 7 / Rolldown

git clone https://github.com/gowthamrdyy/Fairpay.git
cd Fairpay

npm install

Copy the example environment file:

cp .env.example .env.local

Add your Gemini API key (optional for LLM negotiation drafting; heuristic templates work without it):

VITE_GEMINI_API_KEY=your_gemini_api_key_here

npm run dev

npm run build

• Data Attribution: The dataset provided in this demo is a curated sample distribution across major Indian tech roles and hubs.
• Estimation Logic: The Salary Estimator uses a transparent heuristic model rather than an opaque black-box regressor.
• Privacy First: All calculations run locally in the browser with zero identity tracking or tracking cookies.

• Gowtham Reddy — LinkedIn • GitHub
• Hari Prasanna — LinkedIn • GitHub

This project is licensed under the MIT License.