RL env from real data @ooakdata Real data is the most realistic data YC S26
Paris
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Pierre-Louis Vouteau retweeted
Ooak Data is part of Station F's Future 40 this year!
Thank you to the Station F team, our team, our customers and our investors for getting us here. And congrats to the 39 other ones!
@joinstationf #Future40 #StationF
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Come to us if you want to licence your data.
I asked 36 people in AI who to talk to if you're selling a private dataset, like a shut-down startup's data:
19 votes: micro1 (@aliansarinik)
9 votes: Mercor (@BrendanFoody, @adarsh_exe, @suryamidha)
5 votes each:
- Handshake (@GarrettLord, @benmchristensen, @scottringwelski)
- SF Data (@brandonguo, @faizsiddiqii)
4 votes: Surge (@echen)
3 votes each:
- AfterQuery (@CarlosGeorgescu, @spencermateega)
- Ooak Data (@PLouisV, @ThomAub, @adeRL_g)
2 votes each:
- DataVendor (@seeklis, @parth220, @jayendra_ram)
- Grepped (@eriknewsha)
- Nyne (@michaelfanous1, Emad Fanous)
- Standard Data
36 people voted. People couldn't pick a company they work at or founded. Grepped received one negative vote as well. Disclosure: on this list, I'm a small investor in AfterQuery, Fleet, Ionic, Nyne, Ooak Data, Patronus, and SF Data. I didn't vote.
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Pierre-Louis Vouteau retweeted
Most AI agents are trained in fake offices. We build digital twins of real ones.
What’s a digital twin? A copy of a real company, with the same tools, workflows and code, where AI agents learn to do real work.
Same people, same structure. All identities are anonymized.
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People confuse Spirit Airlines/failing companies outcome with the value of every task performed inside it.
A failed airlines still had people doing useful work, else it would not generate revenue.
Training doesn’t mean teaching a model to imitate an entire company.
re Spirit Airlines data: if you train a model on a failed airline's emails you will get a model that is really, really great at running a failed airline
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Companies are sitting on years of operational data. AI labs need exactly that to keep improving.
At @Ooakdata we turn your workflows into a new revenue line for your business: earn up to $1M while keeping your IP.
How it works:
1- Get a live estimate of what your data is worth on ooakdata.com/partner
2- Fill a short form about your company
3- Our team reviews your request and gets back to you in 24h.
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If you want in on the data broker thing, this is literally all it is
1. ooakdata.com/partner
2. Call with Chris
3. Done
If you want in on the data broker thing, this is literally all it is
> sign up as a micro1 referral partner and a Polyshares partner so you have your own tracked links
> find a business with 30+ employees and years of records sitting in their systems
> check the Wayback Machine for 3+ years of company history before you email anyone
> send the owner your link
> let the buyer evaluate the company and price the deal
> get paid up to $50K per completed micro1 referral, or a share of deal value on Polyshares
We submitted 46 data deals in 3 weeks doing exactly this and 13 are moving to next steps
The article has the whole process, the email I send owners and the earnings math, so read it next if you want to capitalize on this. Links in the comments
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Three months, one batch, a lot of late nights in SF.
We came to @ycombinator with @ooakdata to bring company workflows to AI training. Turns out a lot of companies are ready for it.
Now the real work starts, and we're hiring in SF and Paris.
👇 link in comments
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Grateful to be on @chrisbarber "most insightful people in AI" list, alongside people I learn from every week.
@Ooakdata
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Pierre-Louis Vouteau retweeted
prediction: more labs will self-identify as data research labs
the overton window has shifted - data was perceived as "plumbing," but now it's sayable (including at frontier labs) that the data is the research!
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Killer team!
Today we're launching @CautionHosting, a hosting platform for software you can't afford to have hacked.
Deploy sensitive workloads to secure enclaves in minutes and give customers cryptographic proof that prod is running the exact release you approved, not an opaque binary you have to trust.
Caution is built for payment processors, healthcare platforms, AI agents and inference, crypto infrastructure, and other sensitive systems. It removes the blind trust software runs on today: trust in the cloud host, in production admins, in CI/CD, and in the assumption that the code you reviewed is the code actually running.
We spent years securing systems responsible for over $600B in assets and hit the same wall every time: teams couldn't prove what was running in production. Now that AI can find and exploit zero-days faster than anyone can patch, "trust us" isn't enough. Infrastructure has to stay secure even when it's compromised, and prove it.
Verifiable compute becomes the default, like HTTPS did.
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François nails it perfectly. We need to hear more about data success stories.
~$100B of market cap has been created focused solely on selling data to frontier labs..
Scale AI ($29B), Surge AI ($15B), Mercor ($10B), Handshake ($3.3B), Invisible ($2B), Hive ($2B), Snorkel AI ($1.3B), Turing ($1.1B), Labelbox ($1B), micro1 ($500M), etc etc ...
So on 8.12, @ycombinator is hosting a YC Paper Club in Mountain View focused on the most important driver of AI progress: Data
Who wants to come? Who should present?
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If you are an early founder, you should apply to YC.
The YC deadline is Monday. My challenge for college students trying to find a startup idea: what is *newly* possible?
not just with LLMs, or with Dec 2025’s coding agents, but with July 2026’s technology. We can now solve unsolved math problems with a few prompts.
What ideas were previously impossible that are now plausible?
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Pierre-Louis Vouteau retweeted
The YC deadline is Monday. My challenge for college students trying to find a startup idea: what is *newly* possible?
not just with LLMs, or with Dec 2025’s coding agents, but with July 2026’s technology. We can now solve unsolved math problems with a few prompts.
What ideas were previously impossible that are now plausible?
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Pierre-Louis Vouteau retweeted
I thought data companies are going to die, I was wrong. Instead, they might end up being the kingmaker. They’re selling shovels.
They are going to continue growing a lot more. Surge will probably have the reputation of Anthropic in less than 18 months.
Compute is no longer a sustainable edge, researchers change labs & carry their experience with them - data is THE differentiator.
Labs will be forced to buy a lot more data & vertically try to penetrate different industries.
This has already been proven with Anthropic’s focus on coding. But GitHub for other industries don’t exist.
Data companies with strong research muscle & domain expertise will dominate. As intelligence penetrates enterprises a lot more, their dependence on a few labs will reduce as well.
It’ll be extremely difficult for other companies to pivot into this business because the combination of operational muscle + research you need can’t be built overnight. That DNA is critical to do this work.
We of course have a million companies doing this business but extremely few that genuinely push the frontier forward.
We “need” a lot more of those who can partner closely with labs to help build the most critical technology of our lives.
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Pierre-Louis Vouteau retweeted
New Anthropic research: A global workspace in language models.
Of everything happening in your brain right now, only a tiny fraction is consciously accessible—thoughts you can describe, hold in mind, and reason with.
We found a strikingly similar divide inside Claude.
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