Perle Labs

Building the sovereign intelligence layer for AI. $17.5M backed by @hiFramework, @coinfund, @HashKey_Capital, and more. Supported by @PerleFDN.

[Perle Labs @PerleLabs]

Everyone’s racing to build bigger models.

Fewer people are asking what those models are learning from.

Scraped data → noise
Synthetic data → echoes
Verified, human-validated data → signal
The next leap in AI won’t come from more compute. It’ll come from better data.

That’s the layer we’re building.

[Perle Labs @PerleLabs]

The Perle team is back from @token2049, and one takeaway stood out:

AI can generate millions of synthetic examples.

But more data doesn’t automatically mean better data.

Who’s checking for errors?
Who’s evaluating edge cases?
Who’s validating the outputs?

Synthetic data can help solve the scale problem.

Human expertise helps solve the trust problem.

[Perle Foundation @PerleFDN]

The wait is over. $PRL is officially unlocked.

If you selected the 100% six-month lock option during the original claim, your allocation is now available.

Now open: https://t.co/obUpZqOmEb

[Perle Foundation @PerleFDN]

The countdown is on!

$PRL unlocks on Sept 21 at 11:00 AM UTC.

If you chose the 100% six-month lock option, make sure you’re ready:

→ the same Solana wallet used for your original claim
→ enough SOL for network fees
→ access to complete palm re-verification

[Perle Labs @PerleLabs]

https://t.co/yXqqyJqZIQ

[Bitget @bitget]

Put your idle assets to work with Bitget Simple Earn.

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[Perle Labs @PerleLabs]

3/ We’re bringing expert-led model evaluation and data intelligence to help improve Nusuk’s accuracy, contextual understanding, and conversational experience.

The future of enterprise AI will be built on trusted data, refined by human expertise, and designed for the real world.

Read more: https://t.co/dKwwqKOu5w

[Perle Labs @PerleLabs]

1/ Exciting news! We’re partnering with @elm to enhance Nusuk, the Kingdom’s intelligent assistant for Hajj and Umrah 🤝

Nusuk helps pilgrims plan, navigate, and complete key parts of their journey through natural, conversational AI.

AI is moving into real-world moments that truly matter.

[Perle Labs @PerleLabs]

2/ At this scale, the bar is higher.

Nusuk needs to understand language, context, culture, and real user intent, then respond in a way that feels accurate, helpful, and human.

That’s where Perle Labs comes in.

[Perle Labs @PerleLabs]

https://t.co/fUUcM4rHyn

[Perle Labs @PerleLabs]

3/ Perle provides human-verified data infrastructure to help AI teams train, evaluate, and improve intelligent systems with greater confidence.

Samsung’s AI roadmap reflects where the market is heading:

AI built for real-world scale needs data built for trust.

Get the details: https://t.co/CUgcZQzc1q

[Perle Labs @PerleLabs]

Big News: Perle Labs is supporting @Samsung’s next era of AI 🤝

Samsung is advancing AI across one of the world’s most expansive technology ecosystems, from connected devices and enterprise systems to real-world operations.

At that scale, AI needs more than powerful models. It needs trusted data.

[Perle Labs @PerleLabs]

2/ At Samsung’s scale, AI data needs to do more than train models.

It needs to support:

→ Context-aware experiences
→ Multimodal understanding
→ Continuous improvement across products and systems
→ Reliable performance in real-world environments

As AI expands, the quality of the data behind it becomes critical.

[Perle Labs @PerleLabs]

For AI used in healthcare, robotics, law, infrastructure, or defense, every decision should be traceable back to verifiable human judgment.

That requires more than high-quality data. It requires expert-validated contributions, transparent attribution, and full lifecycle audit trails.

[Perle Labs @PerleLabs]

A data label records a decision, but not the judgment behind it.

Provenance shows who made it, whether their expertise was verified, and how the decision was validated.

In high-stakes AI, an answer without that audit trail is still a black box.

[Perle Labs @PerleLabs]

Useful provenance should show:

→ where the data came from
→ who contributed or evaluated it
→ whether their domain expertise was verified
→ how the decision was reviewed and validated

It creates a verifiable link between the data, the human judgment behind it, and the process used to establish its quality.

[Perle Labs @PerleLabs]

Data quality is only part of the equation.

When AI is being trained and evaluated, there are a few questions worth asking:

- Can each contribution be traced?
- Who contributed the data?
- Was their domain expertise verified?
- Is there a verifiable audit trail of how it was produced and validated?

For high-stakes AI, “high-quality” data isn’t enough.

It needs to be expert-validated, traceable, and auditable.

[Perle Labs @PerleLabs]

https://t.co/Asxk1LNDny

[Perle Labs @PerleLabs]

What is one task you would trust AI to help with, but never let it complete without a human review? 🤔💭

Reply below ↓

[Perle Labs @PerleLabs]

FYI, the Perle app got a glow-up 👀

Fresh new colors, plus the Contract Intelligence quest waiting for you to complete.

Check it out: https://t.co/o7v3LqS1Bp