XYO’s Markus Levin: Why a Data-Native L1 Could Become AI’s ’Proof of Origin’ Backbone

Forget the hype—blockchain's real AI play isn't about generating cat memes. It's about proving where the data came from in the first place.

XYO co-founder Markus Levin argues that the next critical infrastructure layer won't be built by the big cloud providers. It'll be a data-native Layer 1 blockchain, purpose-built to be the unbreakable chain of custody for the world's artificial intelligence.

The Trust Gap in the Machine Mind

AI models are only as good as their training data. Yet, in a digital Wild West of scraped content and synthetic generation, verifying a data point's origin is nearly impossible. This isn't just an academic problem—it's a multi-trillion-dollar liability waiting to happen.

Levin's vision cuts through the noise: a blockchain that doesn't just record transactions, but cryptographically stamps every byte of data at its source. Think of it as a birth certificate for the digital age, creating an immutable ledger that answers the fundamental question: 'Prove it.'

Bypassing the Legacy Middlemen

Traditional data verification is a slow, centralized game—perfect for consultancies to bill by the hour. A dedicated L1 bypasses that entire racket. By baking proof-of-origin into the protocol's core, it automates trust. Smart contracts become the auditors, and the chain itself is the notary public.

This architecture doesn't just support AI development; it becomes its foundational truth layer. Need to verify the training data for a medical diagnostic model? Check the chain. Legal challenge over a generative AI's output? The provenance is on-ledger.

The Cynical Finance Take

Of course, Wall Street will try to package this 'digital truth' into another convoluted derivative—because why solve a problem simply when you can securitize it and charge a 2% management fee?

The real value isn't in another speculative token. It's in building the rails that make AI accountable, auditable, and ultimately, usable for mission-critical tasks. In a world drowning in synthetic content and algorithmic bias, the most valuable asset might just be a provable fact. The race isn't to build the smartest AI; it's to build the most trustworthy one.

DePIN’s “every corner of the world” thesis

Levin framed DePIN as a structural shift in how markets coordinate physical infrastructure, pointing to rapid growth expectations for the sector. He cited a World Economic Forum projection that DePIN could expand from roughly today’s tens of billions to trillions by 2028.

For XYO, scale is not hypothetical. One of the hosts noted that the network has grown “with over 10 million nodes,” setting the stage for a conversation focused less on “what if” and more on what breaks when real-world data volume becomes the product.

Proof of origin for AI: the data problem, not just compute

Asked about deepfakes and the collapse of trust in media, Levin argued that AI’s bottleneck isn’t only computation—it’s provenance. “Whereas DePIN, what you can do is you can, uh, prove where data comes from,” he said, outlining a model where data can be verified end-to-end, tracked into training pipelines, and queried when systems need ground truth.

In his view, provenance creates a feedback loop: if a model is accused of hallucinating, it can check whether the underlying input is verifiably sourced—or request new, specific data from a decentralized network rather than scraping unreliable sources.

Why a data-native Layer-1 matters

XYO spent years trying not to build a chain, Levin said—operating as middleware between real-world signals and smart contracts. But “nobody built it,” and the network’s data volume forced the issue.

He explained the design goal simply: “Blockchain can’t bloat… and it’s just built for data really.”

XYO’s approach centers on mechanisms such as Proof of Perfect and “lookback” style constraints intended to keep node requirements lightweight, even as datasets grow.

COIN onboarding: turning non-crypto users into nodes

A key growth lever has been the COIN app, which Levin described as a way to transform mobile phones into XYO network nodes.

Rather than pushing users into immediate token volatility, the app uses dollar-tied points and broader redemption options—then bridges users into crypto rails over time.

Dual token model: aligning incentives with XL1

Levin said the dual token system is designed to separate ecosystem rewards/security from chain activity costs. “We’re extremely excited about this dual token system,” he said, describing $XYO as the external staking/governance/security asset and $XL1 as the internal gas/transactions token used on XYO LAYER One.

Real-world partners: charging infrastructure and mapping-grade POI data

Levin pointed to new partnerships as early “killer app” momentum inside the broader DePIN ecosystem, citing a deal with Piggycell—a large South Korean charging network that needs proof-of-location and plans to tokenize data on XYO Layer One.

He also described a separate proof-of-location use case involving point-of-interest datasets (hours, photos, venue info), claiming a major geolocation partner found issues in its own dataset “in 60% of the cases,” while XYO-sourced data was “99.9% correct,” enabling downstream mapping for large enterprises.

Taken together, Levin’s message was consistent: if AI and RWAs need trustworthy inputs, the next competitive frontier may be less about faster models—and more about verifiable data pipelines anchored in the real world.