Co-Founder, https://xitter.cf/t.co/nipFnTqahu // Enterprise-Focused Data Lab // Exited $35M annual rev Solar Company (2025)

Joined December 2021
If you want to get a piece of this, we just helped a roofing company get a $450k offer for their De-Identified Data. These labs need your workflows to train their models and are paying high dollar right now ($100k-$1M) Dm me if you want to get a quote on your data.
Wow, seems like Google is buying Spirit Airlines' enterprise data for $10m (outbidding Mercor at $7.5m). Basically includes every internal document, email, workflow, and codebase for a once $6B company. Honestly, $10m for 34 years of operational data really seems like a steal.
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If we are hill climbing corn hole then hand me the halo if you need good data.
Frontier VLMs acting as the learning engineer around a robot's learning policy, instead of the primary brain. Video inspired by @GeorgiaChal essay on structure and scale, as well as @GeminiApp 4 Argon's release.
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a 50-person company’s slack and email data is selling for $300-400K right now, and the labs are calling brokers on fridays saying they don’t care what it costs. here’s everything from our conversation with data broker ryan lock (sponsored by Ahrefs): ryan sold his solar company ($35M revenue, 1,000 reps) last year and stumbled into data brokering when someone told his co-founder he could license his company data. the first offer gave him two days to accept or it exploded. his co-founder negotiated it up 4x. that gap is the whole business: the labs are desperate, business owners have no idea what they’re holding, and nobody’s advising the sell side. he launched in july, went viral once, and was doing 15 meetings a day with business owners. team of 13 now. every single lab reached out to him inbound through X. the model is simple: buy data assets from companies, package them into training sets for frontier and mid-tier labs. what they want is operational data: email, slack, drive, accounting, shopify, klaviyo. raw text, not photos or video. the part nobody understands: it’s not volume, it’s context. a customer email that gets pinged into slack that gets resolved in a ticket is a complete story a model can learn from. switch from slack to discord two years ago and lose the chain? the data’s worth a fraction. ryan’s own solar data was nearly worthless because everyone just picked up the phone. his co-founder’s remote slack-native team got the full ask. the numbers: average deal is $300-400K for a 50-100 person company, deals go up to $2-4M for the big ones. quick valuation proxies are number of software tools, years of full-context data, and headcount, because a hundred people generate idea-discussion-approval-feedback loops that five people in one office never write down. the de-identification alone costs $10-50K per terabyte, done by a third party who never lets ryan touch the raw files. and don’t try to scrub it yourself: tony becomes “employee six” everywhere consistently, or the whole set is destroyed. ryan’s analogy for margins: raw data is oil at $100 a barrel, the labs turn it into jet fuel at $2,000, and the broker takes the risk that the barrel has no engine inside. the spirit airlines bankruptcy sold its data to google for $10M, which he thinks is low for the largest public deal. the data companies are all talked about as very profitable, but the real edge is procurement on demand: he forecasts what the labs will want next and ranks his pipeline by acquisition priority. current requests: circuit board CAD files, architecture firms, heavy construction, and video game 3D development. the gotchas before you sell: never sign a perpetual exclusivity. perpetual use is standard (nobody can track files down the chain), but exclusivity should be termed, usually two years, or you’re locked out of a future revenue stream forever. and if you’re selling your business in the next year or two, a $500K data deal can become a due diligence landmine on a $20M exit. tom’s referrals keep saying exactly that. micro one pays $50-75K referral fees because they’re playing a different game. ryan pays 6% and tells brokers to charge the seller for running the process instead. where it goes next: ryan thinks the buyer pool expands past the frontiers to enterprises training their own models. a 20-person HVAC company only knows what it knows, but add 150 years of industry data and you’ve got a vertical model, the harvey-for-law playbook in every trade. the video side is wilder: labs pay $10-20 an hour for people to wear headcams doing manual work, and there are state-sponsored warehouses in china and every low-cost country where workers rotate through sewing and dishwashing stations for robot training. jacky’s fraud prediction: 500 fake chinese companies with active linkedin pages. ryan’s answer: if the simulation is that good, the data’s probably valuable anyway. bonus: jacky’s own slack community, 500 people and 20K messages a month, has already gotten offers. “no amount of money, well, that’s a lie, I’d take my pants off for seven figures.” the over/under for ryan’s next 12 months was set at $300M gross, and micro one just passed a billion annualized. tom asked to become a master affiliate and jacky immediately called it master and slave. tony’s response: “the white guy’s still on top. we went back a hundred years.” the industry is a gold rush and the shovels are already being sold. NGMI with @itstonyyu and @tomwang24, guest @RyanLockAI. watch/listen ↓
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Ryan Lock “RL” retweeted
What if the real data, was the friends we made along the way.
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🚀Polyshares is Hiring! 🚀 Open Roles Product Development - UI/UX Designer reports to CPO (Remote) - Full Stack Engineer reports to CPO (Remote) Data Desk - VP of Lab Partnerships (Remote) Operations - General Counsel (Remote) DM me which role you are interested in and why you would be a force multiplier in that department.
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What if the real data, was the friends we made along the way.
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Actionable guide from one of our top broker partners. Can’t believe he posted all of this
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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Ryan Lock “RL” retweeted
Excited to announce I’m building @Polyshares with @RyanLockAI Polyshares is an enterprise data lab focused on operational and physical AI training data We’ve quickly grown to an 8 figure run rate by being the best procurement partner for AI labs In the past week alone, we’ve onboarded 250+ companies, 200+ referral partners, and 7 new team members. If you’re interested in data, let’s jam
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Come grow with us!
Excited to announce I’m building @Polyshares with @RyanLockAI Polyshares is an enterprise data lab focused on operational and physical AI training data We’ve quickly grown to an 8 figure run rate by being the best procurement partner for AI labs In the past week alone, we’ve onboarded 250+ companies, 200+ referral partners, and 7 new team members. If you’re interested in data, let’s jam
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Ryan Lock “RL” retweeted
NEW: AI labs are fueling a *wild* market for your Slack DMs. Mundane work files are perfect training data for AI giants racing to automate white-collar work. Business owners are getting six-figure 'exploding offers' for their records, with 48 hours to say yes.
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Go read the new Business Insider Article! businessinsider.com/ai-train…
Replying to @CharlesRollet1
Companies are sitting on vast troves of internal data without realizing its value. Data brokers are now hunting for these businesses, and it's getting competitive. @RyanLockAI compares it to the Texas oil boom of the early 1900s:
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Selling data to AI Companies just got safer! Polyshares and @UseCorgi have partnered to protect Polyshares and its data partners from claims over how that data is used in AI Training.
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Corey was one of the best hosts I’ve had the pleasure of chatting with. Go check this out!
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)
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Larissa has joined us as an Acquisitions Associate and has impressed in her first week. Go give her a follow if you want to hear more about the ‘behind the scenes’ at Polyshares
I honestly love working at Polyshares. What we've been doing here is f* amazing. We will revolutionize this market soon. You all will see it!
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Over 1,000 people bookmarked my post about being a good sell-side data broker. I agree with Ali on the future of Data as a revenue stream. The industry needs more talented and ethical individuals helping sellers navigate the licensing process. The best offer is not the one that pays the broker the most. The best offer may not be the one that pays the company the most. The best offer is the one that protects the seller, has fair terms + timelines and restricts the export of US data🇺🇸 to our adversaries. True professionals will be a value add to the transaction and guide their clients through the important contract terms I covered in my article below. There is an incredible amount of money to be made, but with that a greater responsibility to act ethically and represent the company’s best interests. xitter.cf/ryanlockai/status/2107…
licensing data will become one of the most common revenue line items for companies worldwide, similar to how ads became a default monetization model. for many companies, it will become core to the business.
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I would be surprised if by the time they come out of stealth we haven't already clipped the same RRR. The team over there is great. I'm just confident in the Polyshares team to build and execute.
Fastest company ever to $1b annualized revenue Nope it’s not Higgsfield or Cursor or Cognition. Met a data company yesterday that did 0 revenue in November 2025 and 80m “in month revenue” in September 2026. They will hit $1b annualized from 11 months of being started. They are still under the radar so I can’t share who they are. Hopefully soon, with their permission. I don’t make the rules.
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