Hapnin
Events discovery platform with multi-source ingestion, canonical event modeling, dedupe, trust labels, and city-based browsing.
The story
A production case study in turning messy, scattered event data from many sources into one clean, browsable feed.
The concept
Backend cron jobs and webhook listeners sync and deduplicate event data from multiple source APIs into a canonical model, with AI-assisted normalization and trust labelling.
Related work
All workAegis-X
Privacy-first AI security platform that detects phishing and business email compromise without exposing your private data to external LLMs.
Attest
Zero-knowledge compliance verification network on Avalanche L1s, enabling privacy-preserving attestation across chains.
SchemaFlow
Public demo that turns messy web content into structured records: crawl a URL, extract with an LLM into a chosen schema, dedupe, and store.