AI-native infrastructure for real-world data. Formerly known as Story.
Joined December 2021
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Building Trace at scale means making deliberate choices about where we invest our resources.
Joining the Sui stack gives us the infrastructure to grow while keeping our focus on the products and applications driving real adoption.
@devrelius on our next chapter ↓
Verifiable data infrastructure is coming to enterprise AI and finance with @spaceandtime.
Proud to be a launch partner as we continue building toward a future where data provenance, privacy, and verifiability are foundational to AI.
Our very own @devrelius will be live on @TheEdgeofShow shortly.
Tap in ↓
AI runs on data, but who gets to own it?
Josh Kriger with Andrea Muttoni (@devrelius) of The Data Foundation on the next Edge Live. We're getting into a topic that deserves more attention.
📅 November 5 | 1:30 PM CST
Watch live on YouTube, X & LinkedIn.
More teams are starting to think seriously about the infrastructure Physical AI will require.
Good to see PAGI entering the conversation.
xitter.cf/pagifdn/status/2118386…
TLDR: use trace.datafdn.org
I went through every data vendor that launched in the last 3 weeks. Almost all of them are lying about their revenue, their lab partnerships, and their backgrounds.
(skip to 1:04 if you want to skip context)
Too many founders and VCs have been fooled by these people. Stop believing everything you hear. Data is much harder than most people think.
The DATA Foundation retweeted
The sad truth is so many data deals nowadays are complete bullshit
Duplicate data originally sold as "exclusive" gets distributed everywhere and labs have little to no way of checking this
All these data vendors are repackaging existing data and faking partnerships
Spot on 💯
I went through every data vendor that launched in the last 3 weeks. Almost all of them are lying about their revenue, their lab partnerships, and their backgrounds.
(skip to 1:04 if you want to skip context)
Too many founders and VCs have been fooled by these people. Stop believing everything you hear. Data is much harder than most people think.
The DATA Foundation retweeted
Our friends at @otodotearth are searching for contributors to support AI Training via video chats.
See post for details ↓
We're looking for people to help train AI through video chats with a friend!
Up to $50/h per eligible recorded hour, per person.
10-minute chats. US residents 18+. Face and voice used in commercial AI datasets.
Hours not guaranteed. Eligibility and rates: fiber.oto.earth/?utm_source=…
From finding our focus in AI data to the thinking behind joining the Sui stack
CEO @devrelius went deeper on DATA's next chapter with @helenebraunn for @CoinDesk ↓
Enjoyed speaking with @HeleneBraunn about the thinking behind our recent decisions, what we've learned along the way, and where we're headed next with @SuiFoundation.
Thoughtful piece that captures the bigger picture.
coindesk.com/business/2026/1…
Full article:
coindesk.com/business/2026/1…
The DATA Foundation retweeted
Data exclusivity is a massive problem in the ai training data space.
Vendors sell “exclusive” data to multiple buyers and they can’t verify it’s actually exclusive without some audit trail. That is what Trace is.
If you are buying an exclusive dataset you should be confident it’s actually exclusive. The best way to check is to see if that data already exists on Trace.
Force your data vendor to use Trace and protect yourself!
This is just the start.
soon you'll see more and more AI use cases landing on @WalrusProtocol
THIS IS JUST A START
The DATA Foundation retweeted
100%. This is why what we are doing with Trace is so important.
and you can all now see why we are teaming up with Sui and Walrus.
One of the defining questions of the AI era is going to be “How do you know?”
How do you know what is real when anything can be generated? How do you know what really happened versus what you were told happened? How do you know where a piece of data came from? How do you know it has not been changed? How do you know what an agent actually did on your behalf?
I think about this all the time
Verifiability is going to matter as much as intelligence
The DATA Foundation retweeted
Trace will join the @SuiNetwork stack in order to verify the data lifecycle:
→ Trace as the registry and provenance layer (who, what, where)
→ Walrus allows us to verify its actual contents
→ Seal protects the data and unveils to key stakeholders
The lifecycle of data, as told by the DATA protocol → @SuiNetwork.
The DATA Foundation retweeted
One of the main reasons Sui stood out is they already built a lot of the components needed for Trace to grow as the data layer end to end:
- storage (walrus),
- dynamic access control (seal),
- verifiable (but off chain) compute like inference in TEEs (nautilus).
Sourcing, access control, processing and inference can now be all on the same stack, and Trace’s audit layer can formally prove and verify every single step giving more depth and weight to the metadata it stores in turn becoming a source of truth for AI data.
This is the master plan for Trace.
The DATA Foundation retweeted
A bigger stack for what we're building.
With DATA moving to Sui, builders will be able to tap into provenance, storage, access control, and rights-cleared AI data across one ecosystem.
Lots more to build from here.
DATA is coming to @SuiNetwork.
The DATA Network and Trace are joining the Sui stack, bringing a live supply of rights-cleared AI training data to infrastructure built for AI workloads.
With 250M+ receipts already recorded by Trace, AI labs will be able to source real-world data with verifiable provenance, while @WalrusProtocol provides the underlying storage layer.
Sui Foundation is investing $30 million in the DATA Network, establishing the largest institutional stake in the network, alongside the continuing holdings of PIP Labs and the DATA Foundation. Furthering the alignment, SY Lee, founder of the DATA Network and CEO of PIP Labs, joins Sui Foundation as Strategic Advisor.
In the coming months:
▸ The DATA Network will be upgraded to run as a protocol natively on Sui
▸ Walrus becomes the default storage layer for DATA Foundation apps
▸ $DATA remains the token of the DATA protocol
The next chapter of DATA starts here.
The DATA Foundation retweeted
Trace registers over 3M data receipts EVERY DAY
Currently, we are able to surface tons of metadata related to a receipt's provenance:
- Did the contributor sign ToS/PP?
- Where did the data come from?
- When was it captured/uploaded? By what device?
This is the 1st major step in making the data that apps like @useKled collect SELLABLE to AI labs
But the next step is actually verifying ourselves that this information is true:
- Scanning the file itself to discover its metadata
- Verifying the data wasn't tampered with
- Keeping the original copy
By storing files on @WalrusProtocol, we can verify that every data receipt is what is says it is
And give frontier AI labs the complete confidence needed to purchase data in bulk
Trace turns any company into a data company
Walrus is becoming the default storage layer for @datafdn and Trace, the onchain registry for rights-cleared AI training data.
Trace records where AI training data came from and who owns it.
Walrus stores the original file, keeping it tamper-proof and accessible only to licensed buyers.
Trace has already registered more than 250M contributions and adds over 3M receipts a day, from apps that license data to frontier AI labs.
The next generation of AI will be trained on data from people, making provenance a procurement requirement. Walrus and @SuiNetwork make that provenance verifiable.
Read the announcement: sui.io/blog/data-network-joi…
