Ben Cerchio

Founder @Secludy | - de-identification for RL/data companies selling to AI labs

[Ben Cerchio @ben_cerchio]

if you sell AI training data, see how you compare: we found 159 companies selling data, RL envs and evals, every fact sourced

plus 38 programs that pay companies for their data: https://t.co/a3U4qcTvKz

8 of the 14 that pay companies directly publish a dollar range. most of the rest set terms per deal. unknowns are marked and nothing is ranked

the other page: what each program wants, who qualifies and what it offers: https://t.co/FVD3vdqUS3

missing something, or something wrong? fix it on the site, a person reviews every change

we built this at @Secludy. if you buy, broker or license company data and need the names out before it reaches a lab, dm me

[Ben Cerchio @ben_cerchio]

New daily update shipped to our directory of RL/data companies that buy and sell AI training data https://t.co/a3U4qcTvKz

For today's update:
- We added 5 companies (more to be added tomorrow, stay tuned). These include Replay, Alice, G2i, Flevy, and Sticker
- Replay's programs are now on Who's buying: it pays companies to license their data, plus a referral fee
- @besimple_ai now shows its RL environments for voice
- Removed one company that stopped selling data
- Replay's programs are now on Who's buying: it pays companies to license their data, plus a referral fee

For companies that requested to be added, we are working through a large queue and will be reaching out to some of you for clarification and links to support company details

@g2i_ai @alice_dot_io @StickerCommerce @bmaho2211 @flevydocs

[Ben Cerchio @ben_cerchio]

@sk_2496 Yeah we tag if they are selling RL environments or data. Many sell both. What else do you think it would be helpful for us to include?

[Ben Cerchio @ben_cerchio]

We'll be making daily updates to https://t.co/a3U4qcTvKz which is a directory of RL/data companies selling and buying AI training data

We launched the yesterday and shipped new updates today.
- Better search. You can now search by named customers and city
- New companies (got flooded with requests to add companies, many more to be added tomorrow)
- Funding updates (including @labelbox $100M+ Series E)

[Ben Cerchio @ben_cerchio]

some of the teams you’ll find on it. if anything in the listing is off, you can request an update on the site

@Jerr_Wu (Halluminate)
@MatternJustus (Proximal)
@guohao_li (Eigent)
@B_S_N_Y (Midcentury)
@akkkkiira (Arga Labs)
@_oakgul (Incalmo)
@Shahules786 (Vibrant Labs)
@ArjunRajJain (pre . dev)
@benchflow_ai @veris_ai @hud_evals @Colline

[Ben Cerchio @ben_cerchio]

if you sell AI training data, see how you compare: we found 159 companies selling data, RL envs and evals, every fact sourced

plus 38 programs that pay companies for their data: https://t.co/a3U4qcTvKz

8 of the 14 that pay companies directly publish a dollar range. most of the rest set terms per deal. unknowns are marked and nothing is ranked

the other page: what each program wants, who qualifies and what it offers: https://t.co/FVD3vdqUS3

missing something, or something wrong? fix it on the site, a person reviews every change

we built this at @Secludy. if you buy, broker or license company data and need the names out before it reaches a lab, dm me

[Ben Cerchio @ben_cerchio]

@llmhubdev thanks Nitish, we'll see what we can do here

[Ben Cerchio @ben_cerchio]

@dawufi sure thing, we have a form on the site for requesting fixes/updates https://t.co/FZrIiypT7m

[Ben Cerchio @ben_cerchio]

@Freeman_Lewin thanks for the feedback, we will get this updated

[Ben Cerchio @ben_cerchio]

@launch_llama absolutely, we will be updating this daily. are there any companies we missed or additional information you'd like to see?

[Ben Cerchio @ben_cerchio]

@notmiramurati yeah we're planning to expand the company coverage and include data on who is buying from whom (with public sources)

[Ben Cerchio @ben_cerchio]

@brandon_galang yeah this space is growing like crazy. a lot of companies are still in stealth so I wasn't able to add them to this list

👀 @jongall45

[Ben Cerchio @ben_cerchio]

@cneuralnetwork yeah that's the idea we have in mind. would it be helpful to include data on which AI labs work with which RL/data companies?

[Ben Cerchio @ben_cerchio]

@pmitu yeah for sure, we profiled a company that specializes in this space. check out @Simple_Closure

[Ben Cerchio @ben_cerchio]

@fromcodetocloud yeah this market is growing every day. let us know if there's anyone we missed

[Ben Cerchio @ben_cerchio]

@samtwtss we'll be updating this daily

[Ben Cerchio @ben_cerchio]

@pfernan95dev thanks Pablo! appreciate it

[Ben Cerchio @ben_cerchio]

@babayagatwt love to hear it. let us know if there's anything you'd like us to add to the directory

[Ben Cerchio @ben_cerchio]

@buildwithmaya thanks Maya!

[Ben Cerchio @ben_cerchio]

@rollupceo @polyshares @RyanLockAI Congrats!

[Ben Cerchio @ben_cerchio]

100% agree on 3rd party de-id. we provide this at @Secludy. raw data going to the independent de-id provider before going to the data broker builds trust

[Corey Ganim @coreyganim]

This guy did $1,000,000 in 30 days as an AI data broker.

His model: frontier labs have used all the data on the internet and need private company data to keep improving.

His firm finds businesses with the right data then de-identifies it, packages it, and sells it to the labs.

@RyanLockAI runs one of the hottest startups in this space (Polyshares) and walked me through his entire business model on the pod.

Here's what I learned:

1. Making an intro to a data buyer is only step one. Technical due diligence on how the business actually operates is where the value gets built.

2. Labs buy the full workflow. Client email to internal Slack debate to resolution, including the fixes the team rejected.

3. He targets companies with 50+ employees, 3+ years on the same software, US-based, English. Below 50 employees = fixed legal and diligence costs kill the deal.

4. Remote-first white collar wins. If the work happens on the phone, the lab just sees "ticket created, ticket closed."

5. Depth of history beats raw volume. 20 years in business means nothing if they switched software 3 years ago.

6. Never let sellers de-identify their own data. Names become "employee 632" so relationships survive. DIY versions wreck the value.

7. Use a third party to de-identify. They hold the raw files for about a week, then delete them. That kills the biggest objection.

8. Never sign a perpetual license. 24 months of exclusivity is the typical buyer ask.

9. Time the exclusivity to the exit. Selling in 2 years? Match the term so the new owner inherits a dataset they can license again.

10. Demand rotates. A few weeks ago labs wanted heavy construction. Now it's video game companies.

His 2 key takeaways:

1. Act like a sell-side broker, not a lead seller. Organize and present the owner's data like an M&A deal and you can earn an advisory fee on top of the finder's fee.

2. The buyer pool could explode. If enterprises start training their own models, buyers go from maybe 10 labs to hundreds of thousands.

Ryan is doing this at a level most of the people hyping it on X are not, and we had a blast going deep on it. Go follow @RyanLockAI

(Also available on the Build With AI podcast wherever you get your pods)