WageBrew

WageBrew delivers enterprise analytics tailored for the gig economy to drive smarter and earn more.

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Inspiration

The gig economy is booming, but its workers are underserved by traditional financial tools. We’ve experienced the chaos of juggling multiple income streams, manually tracking shifts, and constantly guessing whether we’re on track to hit financial goals. Worse, opaque platform algorithms can quietly drop base pay by 30-40 % without warning, leaving workers to wonder why yesterday’s route paid $18/hr and today’s pays $12. We wanted to build a solution that gives this growing, diverse workforce transparency and control—something smarter, more personalized, and actually designed with gig workers in mind.

What it does

WageBrew is a financial assistant for gig workers. It tracks income, estimates taxes, suggests optimal shift schedules, and helps users set and reach personalized financial goals. The platform integrates with gig apps via OAuth, syncs real-time earnings, and visualizes progress with a clean, intuitive UI. New fairness features:

Rate-Change Alerts – flags sudden drops in base pay.

Earnings Heat-Map – shows when & where algorithms are paying best.

Fair-Pay Score – a simple badge telling workers if today’s payouts are above or below their historical median.

It even nudges users when they’re falling behind on goals—turning insights into action.

How we built it

We built WageBrew using Next.js 14 (App Router), TypeScript, Tailwind, and Supabase for real-time data syncing. OAuth flows were implemented for multiple gig platforms with platform-specific API routes. Supabase Edge Functions power smart goal tracking, XP rewards, and algorithm-shift detection. We used Bolt AI to co-generate modular React components, design variants, and Supabase services. The app is fully internationalized with next-intl, and the UI adapts for both desktop and mobile-first usage.

Challenges we ran into

Platform integrations – every gig app has a different OAuth flow and sparse docs.

Data modeling – flexible Supabase schemas had to handle custom income sources, goal types, and preferences plus granular pay-rate snapshots for fairness analytics.

Reverse-engineering pay signals – detecting algorithmic rate changes from noisy earnings data pushed our modeling skills.

UX balance – packing powerful insights into a stress-free interface for time-strapped users.

Real-time sync – keeping goals, XP, and shift data in perfect lock-step with Supabase onSnapshot.

Accomplishments that we're proud of

A fully working smart planner that connects user goals to shift suggestions in real time.

Dynamic earnings goals with visual Gamified XP and badge tracking.

New transparency tools—Rate-Change Alerts, Earnings Heat-Map, Fair-Pay Score.

A personalized dashboard summarizing earnings, progress, and upcoming shifts—cleanly, concisely, and in real time.

Collaborating with Bolt AI to rapidly iterate on complex, type-safe UI components.

What we learned

Supabase + Next.js excel for real-time apps—but only with thoughtful data modeling.

OAuth is complex, yet scalable when modularized per provider.

AI coding tools like Bolt accelerate development when paired with human design thinking.

Transparency matters—turning earning data into insights about algorithmic behavior delivers the highest user value.

Gig workers are incredibly underserved—designing for them means prioritizing flexibility, clarity, and speed.

What's next for WageBrew

Income API Integrations – Create partnerships with gig platforms.

Tax estimation engine – real-time, location-aware guidance for 1099 workers.

Community & insights – launch a worker forum, shift benchmarks, and best-practice tips.

Mobile app – cross-platform app for on-the-go shift updates and goal tracking.

Premium tier – advanced analytics, tax reports, and shift optimization.

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