FairGig — Gig Worker Income & Rights Platform
Transparency for Pakistan's Gig Economy
Comprehensive gig economy platform built to bring financial transparency, accountability, and empowerment to millions of gig workers in Pakistan. Addresses critical gaps including lack of unified income records, hidden deductions, and no way for workers to prove earnings to banks or landlords. FairGig provides three distinct role-based dashboards: Worker platform for logging shifts across platforms (Careem, Bykea, Foodpanda) with screenshot verification, Verifier dashboard for reviewing and validating submissions, and Advocate analytics for monitoring commission trends and detecting worker vulnerability. Core features include Z-score anomaly detection to flag unusual deductions with human-readable insights, privacy-first city-level analytics without exposing individual worker data, and print-ready income certificates for real-world use with banks and institutions. Built with 6 microservices architecture (FastAPI + Node.js with shared PostgreSQL database) designed for production-style scalability under hackathon constraints. One-command startup system enables judges to fully run the platform in seconds.
Why it mattered
Gig workers often lack trusted income records, transparent deduction histories, and proof documents for banks or landlords.
What shipped
A role-based platform for workers, verifiers, and advocates that logs income, flags abnormal deductions, and creates income certificates.
Proof signal
Financial transparency for gig workers; Unfair deduction detection using anomaly detection; Income certificates for financial inclusion; City-wide platform accountability; Worker rights & vulnerability monitoring; Real-world problem solving for informal economy
System flow
React dashboards connect to FastAPI and Node services over a shared PostgreSQL store. Worker submissions flow through verification, anomaly detection, and certificate generation.
Honest maturity snapshot
Raw datasets, disconnected metrics, and hard-to-scan findings.
A structured analysis or dashboard with clear KPIs, visual patterns, and decision-ready insights.
Features
- Worker dashboard for shift and income logging.
- Verifier workflow for screenshot-backed submissions.
- Advocate analytics for city-level trends.
- Z-score anomaly detection for unusual deductions.
- Income certificate generation for financial inclusion.
- Privacy-first aggregation rather than exposing individual workers.
Engineering challenges
- Designing useful analytics without compromising worker privacy.
- Making a complex multi-role system understandable under hackathon time pressure.
- Balancing demo polish with production-style architecture.
Results
- Created a credible civic-tech product narrative.
- Showed ability to design for real users, not only technical demos.
- Proved comfort with multi-service architecture under constraints.
What I learned
- Tradeoff learned: Designing useful analytics without compromising worker privacy.
- Proof learned: Created a credible civic-tech product narrative.
- Next iteration: Add worker consent and data export flows.