The Revelation: Final Form of DYOR AI

From Research2Earn to Research-as-a-Service

Back in Article 3, we showed how Research2Earn started as a bold experiment. A bet on human curiosity. A structured path from “I want to earn” to “I want to understand.” We didn’t preach DYOR. We turned it into a skill. One that could be learned, practiced, validated, and rewarded.

And the result? It worked.

Today, every weekly DYOR Digest is packed with submissions. Quarterly reports are shared, reposted, dissected. Founders read them. Some rewrite tokenomics based on them. Others open calls with our researchers to debate their conclusions.

What started as a community initiative became a real source of value.

And then something unexpected happened.

B2B players started asking for our data. APIs, direct integrations, regular feeds. Not just to read — but to build on top.

But that was only half the story.

Because in parallel, something bigger was growing: the retail audience. People who don’t want to join the Trust Army, but still want to survive web3. People flooded with social campaigns, retrodrops, and token races. People who ask:

“Should I even touch this project?”

They don’t need 15-page reports. They don’t need academic frameworks.

They need an entry point.
A context.
A signal.

Something fast, clean, and trusted.

And that’s where we made the pivot:
From Research2Earn to Research-as-a-Service.
From reports for readers to tools for everyone.

The Power of AI-Driven Decision Making

But then came the harder question:
Why not just scale the research community?
Why AI?

The answer starts with bias.

Even the best researchers bring perspective. That’s part of the magic — but also a limit. Two people can write two great reports… and reach two opposing conclusions. Multiply that by hundreds? It becomes noise again.

This variability underscores the need for a system that can synthesize diverse viewpoints into coherent insights.

Moreover, human analysis has its limitations. According to our internal surveys:

• Only 40% of individuals check a project’s audit status during their research.
• Merely 30% investigate the backgrounds of project founders.
• Alarmingly, 81% have experienced a rug pull at least once.

These figures highlight a significant gap in due diligence practices, contributing to the staggering $2.9 billion in losses reported in the Web3 space in 2024, based on the Hacken Security Report

Now add another layer:
Decay.

Data in Web3 doesn’t stay fresh.

• Tokenomics change after IDO.
• Founders rotate.
• TVL inflates with farm incentives.
• Audits get published, bugs get patched.
• Сommunities die.
• GitHub goes silent.
• etc.

Try applying that to 9,799 projects on CoinMarketCap.
Now try doing it across 40+ data layers per project.
Now try delivering conclusions, not dashboards.

That’s why this couldn’t be manual anymore.
This needed to scale like the space it’s built for.

One Click, All the Answers: The Future of DYOR

The future we’re building is simple:
You enter a ticker.
You get a conclusion.

Not a feed. Not a data dump. Not a thread.

A real-time, bias-resistant, dynamically updated insight — powered by:

• Historical datasets from the Trust Army.
• Expert-curated logic from Alpha Intelligence.
• Real-time 3rd party APIs (CMC, Coingecko, GitHub, KOL metrics, etc).
• Cross-checked human-labeled conclusions from certified researchers.

No signup. No dashboard.
Just one click. One line. Your decision, your timing.

It’s not financial advice.
It’s not a verdict.
It’s your entry point — but one backed by more thought than 99% of crypto.

Because we all know:
People are busy.
People are overwhelmed.
And the myth of the “everyone DYORs” user? Let’s be real.

The Bybit x Toluna Joint Research Report reveals:

• 31% of investors rely on social media as their primary source of information.
• 24% depend on advice from friends or family.
• Only 11% consult official project documentation.

These statistics indicate a reliance on potentially unreliable sources, leading to uninformed investment decisions.

DYOR AI aims to change this narrative. By aggregating data from trusted sources and presenting it in an accessible format, it empowers users to make informed decisions with minimal effort. Whether you’re a seasoned investor or new to the crypto space, DYOR AI provides a reliable starting point for your research, reducing reliance on hearsay and increasing confidence in your investment choices.

A New Standard for DYOR Reports

The shift is bigger than we thought.

Because suddenly, founders started referencing DYOR insights in their own pitch decks.
VCs started pinging us for red flags.
Wallets asked how to display research scores.

And that’s when it hit us:

DYOR AI isn’t just a better way to do research.
It’s becoming a new standard for what counts as credible.

Just like Etherscan defined “on-chain transparency” years ago — 
We’re building the layer that defines “research clarity.”

And yes, it will plug into wallets.
And yes, it will integrate into trading AIs.
And yes, learning dApps are already testing it.

But its real power?
It’s the signal beneath the chaos.
The checkpoint before you act.
The reflection of 1,000 minds — streamlined into 1 insight.

Closer Than Ever

We built Research2Earn to teach the world how to research.
But DYOR AI?
It’s how we’ll teach the world to trust again.

Not through hype.
Not through narratives.
But through a system that sees clearly, even when we don’t.

We’re close.
And next time you type a ticker, you won’t be guessing anymore.
You’ll be seeing the future of DYOR.

Get real research, not hype.
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