SpeakWise

SpeakWise is a platform that brings structured, data-driven feedback to public speaking. Speakers get actionable analytics on their performance, organizers discover talent based on real data instead of reputation alone, and attendees give anonymous feedback that actually drives improvement.

What I Built

My focus has been on the backend infrastructure powering the platform:

• Feedback API: Endpoints for collecting structured, anonymous feedback across multiple dimensions - delivery, content quality, engagement, and actionability.
• Analytics pipeline: Aggregation logic that transforms raw feedback into trends, strengths, and growth tracking over time.
• Speaker profiles & discovery: Backend services for building data-backed speaker profiles and enabling organizer search by topic expertise and performance metrics.
• Auth & role management: Multi-role system allowing users to switch between speaker, organizer, and attendee contexts.
• Database design: Postgres schemas supporting the feedback, analytics, and user management layers.

Architecture & Technical Decisions

The platform splits into a Next.js frontend and a Python backend API backed by Postgres. Feedback submitted against a talk is written through the feedback API, persisted relationally, and then rolled up into the per-speaker analytics that power profiles, trends, and organizer discovery.

Why It Matters

Most speakers operate blind - they finish a talk and have no idea what landed and what didn't. SpeakWise closes that loop with real data.