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# Projects Database
Codename: `PrivacyBeat`
Codename: `PrivacyBeat`
Brief: A ranking system that empowers the general public to discern the privacy levels of various Web3 projects.
Aim: to assist users in making informed decisions about the services they choose to trust.
[Live demo:](https://taikai.network/ethrome/hackathons/ethrome-23/projects/clng508ts00lswu01030hpfuq/idea)
In the digital age, privacy is not just a priority but a fundamental human right. Motivated by this belief, we are pioneering the development of an innovative scoring system, incorporating both expert analysis and community input, to offer impartial resources for evaluating projects.
### Why this is important / Market fit
Despite the foundational role that privacy is meant to play in shaping Web3, genuinely impactful initiatives remain scarce. Many projects leverage the concept of privacy as a buzzword or for public relations advantage, rather than addressing tangible issues or enacting substantial changes at the infrastructural and transactional level.
That's why a ranking system of all privacy-related projects in the Web3 could help a lot the users to discern.
### References:
- [l2beat](www.l2beat.com)
- [certik](www.certik.com)
- [metacritic](https://www.metacritic.com/about-metascores)
- [Clutch](https://clutch.co/methodology)
### More details about the Scoring Mechanism:
Professional scoring would be a joint R&D with the key web3 people from protocol architects to security specialists. We are collecting feedbacks from privacy experts from the Ethereum Foundation, Railgun, Waku, NYM... while building on the experience of active members from both solar and lunarpunk communities. This will help to create an unbiased take from scratch & enabling a transparent working process, accessible to everyone via a forum.
In parallel to the top-down scorecard method, we'll develop and implement a bottom-up community scoring platform too (think of Metacritic exters + users scorings) -> at the end of the day it's the users who have to become the real watchdogs of the industry, signaling about flaws and shortcomings of solutions.
We interviewed 100 privacy players & gathered an MVP vision — we are running a series of 1-on-1 feedback loop sessions to make the scoring model community validated.