Nexa
Dual-mode ZPIE privacy analytics engine for Zcash
Created on 4th December 2025
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Nexa
Dual-mode ZPIE privacy analytics engine for Zcash
The problem Nexa solves
Blockchain analytics tools are either easy to use but not private, or privacy-preserving but too complex for normal users. Public dashboards can’t analyze Zcash’s shielded activity safely, and existing privacy tools require deep cryptographic expertise, complex setups, and provide no readable insights.
Nexa solves this by combining public analytics with fully encrypted privacy analytics powered by FHE (CoFHE), nilDB, and nilAI. It lets users:
- Understand Zcash activity without exposing sensitive data
- View private network trends computed entirely on encrypted data
- Get clear AI summaries using safe embeddings, never raw values
- Monitor privacy health, anomalies, and shielded metrics with strong guarantees
Nexa makes advanced, privacy-preserving blockchain analytics accessible, safe, and easy to understand for everyone.
Challenges I ran into
One challenge was learning how to work with encrypted analytics for the first time. FHE computations don’t behave like normal arithmetic, and early results were incorrect due to scaling issues.I solved this by adopting a consistent fixed-point encoding strategy and batching all values into a stable vector format.
Another hurdle was CoFHE’s asynchronous job model.
Results don’t come back immediately, and some were initially lost or returned out of order. Adding a simple job queue, retry logic, and storing metadata alongside ciphertexts in nilDB stabilized the workflow.
Finally, the 3xpl sandbox API had rate limits and occasional gaps in data.
Implementing caching, backoff, and graceful fallback windows made the ingestion pipeline reliable.
Tracks Applied (5)
Zcash Data & Analytics
Fhenix
Privacy-Preserving AI & Computation
nillion
Zcash Data & Analytics
nillion
Zcash Data & Analytics
Raybot
General Bounty
Project Tachyon
Technologies used
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