The Problem
Data is Abundant, Trust is Not
Most modern datasets suffer from at least one of the following issues:
- Scraped from the open internet
- Biased toward vocal or extreme users
- Outdated or unverifiable
- Collected without clear consent
- Tied to personal identifiers
As a result, teams often make decisions based on assumptions rather than evidence. This leads to poor product design, inefficient growth strategies, and unreliable AI systems.
Raw Data Creates Risk
Storing raw user data introduces significant challenges:
| Challenge | Impact |
|---|---|
| Privacy and regulatory exposure | Legal liability under GDPR, CCPA |
| Security liabilities | Breach risk and data theft |
| High infrastructure costs | Storage, processing, compliance overhead |
| Ethical concerns | Surveillance-style data collection |
Many organizations do not need raw data. They need answers.
Users Are Excluded from Value Creation
Individuals generate high-quality behavioral data through everyday digital activity:
- Ordering food
- Streaming content
- Shopping online
- Using apps
Today, this value is captured almost entirely by platforms, while users receive little control or benefit.
This imbalance is unsustainable.
Myrad Rewrites the Rules
Myrad introduces a new paradigm:
| Shift | What Changes |
|---|---|
| From data hoarding | To signal sharing |
| From surveillance | To consent |
| From raw logs | To human meaning |
We do not fix the old system. We replace it with something fundamentally better.
Organizations get verified, privacy-safe signals. Users retain control and earn rewards. Trust becomes a first-class feature.