</sentinel>
</the problem>
Too many unreliable news sources. People can't track topics across outlets, languages, or verify what they read. Enterprise intelligence tools cost $500+/month, leaving students, journalists, and everyday people with no way to get verified, structured intelligence on any topic.
</my approach>
Built a full intelligence pipeline: Firecrawl scrapes global sources (including non-English with auto-translation), feeds them into Gemini 2.5 Flash for claim extraction and verification, and assembles structured reports with confidence scores. Iterated through 4+ rounds of low-fidelity testing to balance information density with readability.
</key features>
Topic tracking with push alerts
Subscribe to any topic and get notified when breaking developments happen. No manual re-searching.
AI reports with blind spots analysis
Every report includes what the coverage is missing, not just what it says. Confidence scores on individual claims.
Financial charts and timelines
Live market data from Finnhub, event timelines, and candlestick charts embedded directly in reports.
Cross-user SHA-256 cache
Duplicate queries hit a shared cache, cutting API costs 50-80% at scale.
Social discovery hub
User profiles, public report sharing, and trending topics across the user base.
</what i learned>
Balancing information density with readability is the hardest UX problem in intelligence tools. Too much data overwhelms; too little loses trust.
Self-chaining edge functions are a viable pattern for long-running background jobs on serverless platforms.
Building three frontends (iOS, Android, web) on one backend forces clean API design from day one.