DATAHEDGE

Next-generation user-based AI data infrastructure for everything.
Supported by @NVIDIA inception
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[DATAHEDGE @DATAHEDGEAI]

We own 24 million users and 1 billion refined data records, and we plan to provide this data free of charge to all AI startup companies for one month.

Meet Data Hedge now the most powerful LLM user-based data layer.

[DATAHEDGE @DATAHEDGEAI]

🫵✅

[Alpha Seeker @AlphaSeeker21]

VCs are about to pour BILLIONS into specialized AI models trying to build the “Anthropic of Finance,” “Anthropic of Healthcare,” “Anthropic of Insurance,” etc.

But every one of those models needs something.

DATA.

Neobanks have accounting data.

Visa/Mastercard have transaction data.

Lenders have lending data.

Hospitals + insurers have healthcare data.

And as compute gets cheaper, proprietary high-quality data becomes MORE valuable.

That’s why I’m increasingly bullish on $DATA @DATAHEDGEAI.

They’re building infrastructure around turning real human-AI interactions into privacy-preserved, consent-driven data assets.

The first AI trade was GPUs.

The next AI trade could be the data feeding the models.

Data is the next frontier.

And $DATA is positioned directly in front of that narrative.

MC: $84k

CA: AyLn7YdHqh3pGSNC1YrdEtEdSCVjG7BxQedxBvkTpump

[DATAHEDGE @DATAHEDGEAI]

🫡

[Alpha Seeker @AlphaSeeker21]

VCs are about to pour BILLIONS into specialized AI models trying to build the “Anthropic of Finance,” “Anthropic of Healthcare,” “Anthropic of Insurance,” etc.

But every one of those models needs something.

DATA.

Neobanks have accounting data.

Visa/Mastercard have transaction data.

Lenders have lending data.

Hospitals + insurers have healthcare data.

And as compute gets cheaper, proprietary high-quality data becomes MORE valuable.

That’s why I’m increasingly bullish on $DATA @DATAHEDGEAI.

They’re building infrastructure around turning real human-AI interactions into privacy-preserved, consent-driven data assets.

The first AI trade was GPUs.

The next AI trade could be the data feeding the models.

Data is the next frontier.

And $DATA is positioned directly in front of that narrative.

MC: $84k

CA: AyLn7YdHqh3pGSNC1YrdEtEdSCVjG7BxQedxBvkTpump

[DATAHEDGE @DATAHEDGEAI]

Data marketplaces are gaining the most attention in the second half of 2026.

[Alpha Seeker @AlphaSeeker21]

Alpha 👇

$KLED @useKled is already showing the market how valuable the AI Data can become, sitting around a ~$13M valuation.

Now look at what $DATA @DATAHEDGEAI is building.

They just launched Constitutional Data v1.0, an open protocol designed to make AI training data cryptographically verifiable.

Think about what that means:

→ Explicit user consent
→ Cryptographic provenance
→ Human-authorship attestation
→ Privacy-cleaned data
→ Revocable consent
→ Open verification
→ MIT-licensed implementation

AI labs don’t just need MORE data.

They increasingly need to prove where that data came from, who authorized it, and whether they’re legally allowed to train on it.

$Kled is proving that human-generated AI data can be a major market.

@DATAHEDGEAI is trying to build the trust + verification layer for that market.

Instead of:

“Trust us, this dataset is legitimate.”

It becomes:

“Verify it cryptographically.”

If AI Data becomes one of Solana’s next major verticals, I want exposure to the infrastructure underneath it.

$DATA is one I’m watching very closely at this very low valuation. I like the R/R at this MC.

MC: $59k

CA: AyLn7YdHqh3pGSNC1YrdEtEdSCVjG7BxQedxBvkTpump

[DATAHEDGE @DATAHEDGEAI]

Introducing Constitutional Data v1.0 by @DATAHEDGEAI.

AI needs data.
But the next generation of AI infrastructure needs something more:

Proof.

Constitutional Data is an open protocol designed to make AI training data cryptographically verifiable.

→ Explicit user consent
→ Cryptographic provenance
→ Human-authorship attestation
→ Privacy-cleaned & reviewed data
→ Revocable consent
→ Open verification
→ MIT-licensed reference implementation

Every valid dataset can carry a verifiable receipt showing who consented, what they consented to, and whether that consent is still active.

No black box.
No need to blindly trust DATA HEDGE.

Stop scraping. Start signing.

Constitutional Data v1.0 is now open.

https://t.co/MxqyPlTjZg

[DATAHEDGE @DATAHEDGEAI]

GM🌞

[DATAHEDGE @DATAHEDGEAI]

@DataHedgeAI congratulates @solana and @virtuals_io on their official launch tomorrow.

And on @Solana, @DataHedgeAI is the only platform dedicated to verifying AI agents.

Try our AgentEval.
https://t.co/tNVMb9sR3Z

[Solana @solana]

08.24.2026

[DATAHEDGE @DATAHEDGEAI]

The DATA sector is clearly just getting started. U.S. Big Tech companies are now making AI data a core part of their business strategies.

[Insiderwave @insiderwave]

🚨BREAKING

Peter Thiel, one of the richest people in the world.

The co founder of PayPal, co founder of Palantir and early Facebook investor revealed his current investments in the recent 13F filing.

It includes these 8 stocks…

[DATAHEDGE @DATAHEDGEAI]

🤝

[DATAHEDGE @DATAHEDGEAI]

New preparations, a new leap forward. Coming soon…

[DATAHEDGE @DATAHEDGEAI]

We’ll soon find out what the next announcement is.

[Alpha Seeker @AlphaSeeker21]

You can wait for the next announcements, see what @DATAHEDGEAI has been building these past few weeks, and potentially buy at a higher valuation.

Or you can take the leap of faith like I am and position early.

$DATA is building AI data infrastructure with one of the strongest doxxed technical teams I’ve seen at this valuation; a team that has already scaled previous companies to millions of users.

And the thesis is simple:

AI is only as good as the data behind it.

Everyone focuses on the next frontier model, but the data infrastructure feeding those models could be just as important if not more important to the entire AI stack.

That’s the kind of asymmetric R/R I love at sub-$60K MC.

Bullish on $DATA @DATAHEDGEAI

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[DATAHEDGE @DATAHEDGEAI]

The $DATA ecosystem is expanding.

[zen @Zen_EVOLVE]

Datafolio
$data integrity 👏
@DATAHEDGEAI
$DATA integrity
@datafdn
$KLED @useKled

[DATAHEDGE @DATAHEDGEAI]

Additionally, as part of our efforts to advance our @IBM Business Partner tier, we have successfully completed official IBM training programs focused on Data and AI.

[DATAHEDGE @DATAHEDGEAI]

Official Announcement.

@DataHedgeAI has now confirmed that our MSP (Managed Service Provider) agreement is officially Active in the @IBM Business Partner Portal. ✍️🤝

We are now approaching the final stages toward achieving the requirements for the Silver tier and unlocking further co-marketing opportunities with @IBM.

Another major step forward for DATAHEDGE AI.

[DATAHEDGE @DATAHEDGEAI]

📺

[Tech Terminal @TechTerminalx]

Latest News - $DATA

@DATAHEDGEAI has outlined upcoming infrastructure designed for x402-powered agents, enabling them to access and utilize high-quality real-world data across Base and Solana.

The project emphasizes that data is becoming a core resource for the emerging agent economy and is preparing tools to support this demand. Plans include collaboration with a range of agents and agent ecosystems to integrate the new infrastructure into practical workflows. As a next-generation user-based AI data platform supported by NVIDIA Inception, Datahedge continues to position $DATA within the growing pay-per-request agent landscape. The combination of x402 payment rails and structured data access aims to create more functional agent operations.

Community interest is building around the forthcoming data services. Further details on the infrastructure release and partnership activity are expected soon. This direction reinforces Datahedge’s focus on supplying the information layer that autonomous agents require.

For all the latest Solana tech news, check out https://t.co/qwoSAGqe8e. We track and cover updates from over 200+ Solana tech projects in one place.

[DATAHEDGE @DATAHEDGEAI]

🙈

[Khaleepha @YaKhaleepha]

You have probably created valuable AI data without realizing it.

Every prompt you write.
Every correction you make.
Every workflow you build with AI.

That interaction tells us something about how humans actually use AI.

@DATAHEDGEAI is building around that.

DATA HEDGE lets users voluntarily contribute their AI history, clean sensitive information, and turn real human-AI interactions into privacy-preserved data assets.

And the ecosystem is powered around $DATA.

The bigger idea is simple:

AI needs better data.

But that data should come with consent, privacy, and user participation.

That is the part of DATA HEDGE I am watching closely.

$DATA
@DATAHEDGEAI

[DATAHEDGE @DATAHEDGEAI]

Did you know?

Data is becoming one of the core resources powering the emerging x402 agent economy across @base and @solana.

And we’re getting ready for what comes next.

@DATAHEDGEAI will soon introduce new infrastructure designed for x402-powered agents enabling them to access and utilize high-quality, real-world data.

We’ll also begin working with a wide range of agents and agent ecosystems to bring this infrastructure into real-world workflows.

Agents need data.
x402 gives them a way to pay for it.
$DATA is getting ready.

[Brian Armstrong @brian_armstrong]

Set this up and just type /402

[DATAHEDGE @DATAHEDGEAI]

😳🫵✅🤎

[Michael 宝塔镇河妖🧙🏿‍♀️ @quschdnjs]

@AzeyCry @DATAHEDGEAI models for onchain identity finally getting real attention

[DATAHEDGE @DATAHEDGEAI]

The next major sector after AI agents will be DATA.

And it’s much closer than you think.

[aZeiicry @AzeyCry]

Very good explanation, so people can better understand why a model like this is important for the future of onchain identity... @DATAHEDGEAI

$DATA $SOL
DYORR

[DATAHEDGE @DATAHEDGEAI]

https://t.co/VsRn2rSECN

[DATAHEDGE @DATAHEDGEAI]

AgentEval × Claude by @AnthropicAI

@DATAHEDGEAI has implemented a real-world AI agent evaluation pipeline centered around Claude by @AnthropicAI.

AgentEval does not rely solely on synthetic benchmarks. It extracts real-world tasks from privacy-cleaned DATA HEDGE data collected under explicit agent_training consent, then evaluates @claudeai on those same tasks through an automated structured evaluation pipeline.

The evaluation metrics include:

• Real-World Task Performance
• Hallucination Resistance
• Execution Safety
• Decision Quality
• Risk Management
• Human-AI Interaction

The results are converted into standardized S–F grades and published through the AgentEval benchmark and leaderboard.

And this is only the beginning.

The next step is Human Preference Evaluation combining LLM-as-a-Judge with evaluations from real humans to build a more reliable evaluation framework.

Real data.
Claude evaluation.
Verifiable results.