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

Joined December 2021
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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What if the real data, was the friends we made along the way.
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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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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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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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This is notable. DeepSeek, a lab usually first to pioneer novel algorithms and architectures, is saying that at this point, the ROI of improving data quality far exceeds that of working on novel post-training algorithms. I think this has already been true for some time for non-lab practitioners. If you're doing llm post-training, 80% of your effort should go into looking at your data. This means: - Hiring experts to dig through your RL tasks - Sifting through rollouts and sft data by hand to remove suspicious samples. Make sure all tasks are actually passable. - Making sure your data is diverse in both difficulty and category.
🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models. 1/6
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if i had to give one piece of advice to RL data vendors, it would be to focus on a single niche. the biggest issue with naive vendors is that they don't see that the problems are different in each niche. there isn't a single blanket solution to scaling synth pipelines and they try to scale too quickly. many core QA and design principles cross-over, but each domain has its own unique issues that must be hill-climbed. even domain-specific niches have bespoke issues. MLE and inference eng tasks are vastly different to enterprise SWE tasks. banking excel tasks are different from back-office or email tasks. there is SO much variance, each one indexes on a different axis of quality. please focus on quality, it makes all of our models collectively better.
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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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I’m a plumbing company owner and I’m using Grok @bot to automate a ton of office manager work. Here’s what I’ve done in the last 24 hours:
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DFW Peeps, Will be hosting a mixer out at Harvest Hall in Grapevine next Thursday (Aug 13) from 6–9 PM. Super casual, just a pay-your-own-way mix & mingle. Would love for you to drop by! Let me know if you can make it. harvesthall.com/
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I stopped tweeting 2 years ago to touch some grass and build. Now I’m back with two 8-figure companies and a few scars to show for it. I run Roofer com and co-founded AOSwag, AI rollups in roofing and swag. My toxic trait is thinking every industry’s an AI rollup opportunity. If you’re building something cool or just good vibes, say hi :)
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☀️Look at this install from today!☀️ These Vinyl wraps for the panels dispel any curb appeal concerns when going solar.
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I raised $3,000,000 from some of the top leaders in M&A to disrupt the business brokerage industry with a better way to do deals. I've been building in stealth for almost a year. Dealonomy launches Monday. So what the heck is it??? I’ve been selling businesses for a decade and took everything I’ve learned that frustrates Buyers and Sellers, then started with a clean sheet of paper to see if I could solve for both—and create a new kind of tech-enabled, scalable super-brokerage at the same time. But first, let’s take a quick journey back to where I began, so we’ve got context for where we’re going. In 2013, I sold a manufacturing business I helped start and decided to buy an established business for my family using some of the capital from the sale. I had no idea how broken this market was. Days of searching turned into weeks and months of striking out. Ads looked good at first—but then I couldn’t get calls back, couldn’t get complete information, or discovered the details were totally different than the ad led me to believe. Incomplete info. Overpriced deals. Poor representation. It was a nightmare. 😵 That frustration as a Buyer is what made me start a brokerage—the thought of “someone has to do better!” So I created a buyer-friendly firm called Texas Business Buyers and enjoyed real success over the next 7 years, winning awards and building a small team doing good deals for great people in Texas. During the downtime of Covid, I started sharing deal stories and teaching everything I knew about M&A on Twitter. Little did I know, social media was about to change my life and business. People all over the country resonated with the quality-first, transparent approach of Texas Business Buyers, and I quickly became one of the most well-known business brokers on the internet. I got tired of hearing, “I wish your team worked outside of Texas, I’d love to buy a business from you!”—so we rebranded as Bison Business and started doing deals nationwide. (The other quiet shift with Bison: we began offering Buy-Side M&A services and launched a paid deal distribution newsletter for Buyers—which taught us what they valued enough to actually pay for. Up until then, we had only charged Sellers.) Our proven Sell-Side formula was similar to other top independent brokers. We were picky. We turned away 70% of Sellers who approached us, only representing high-quality businesses with clean financials and strong earnings—the kind we’d be proud to buy ourselves. Then we packaged them beautifully and sold them to our Buyer network at a fair price. This made Buyers love us. They knew if they saw our logo, it was a good deal. But the Buyers kept flooding in. “Quit your job and buy a boring business!” was hitting mainstream. Meanwhile, we couldn’t find enough Sellers who met our standards. We were victims of our own success. When we used to get 10–30 interested parties per deal, we were now getting 200–500. And the Buyer database kept growing. Eventually, we realized: our business model was breaking. Having 20x more Buyers and the same number of Sellers didn’t make us more money. It just made us work harder—communicating at scale, disappointing more Buyers—for the same number of closings (since we can only sell each business once). We needed a LOT more Sellers to feed this demand. That’s when I had a chance meeting with Marshall Hatfield, a marketing expert from the real estate world who specialized in sourcing off-market Sellers at scale. That’s when the Dealonomy dream started to come together. If he could get me in front of more Sellers, I knew we had the Buyer network, team, and reputation to close a lot more deals. I had also just read Alex Hormozi’s book “$100M Offers” and realized I didn’t just need more Sellers—I needed to make our pitch a no-brainer. Most brokers, including me, had essentially the same pitch: “Pick me, I’m the best. I charge ~10% at closing and only get paid if you do. I’m worth it because selling a business is hard, and I’m really good at it.” But here’s what we came up with instead: “We’ll sell your business for 0% commission to our large, pre-screened Buyer Network.” If Buyers outnumber Sellers 100 to 1, why give Sellers any reason not to list with us? Actually—why not go one better? Let's offer a guarantee. Over the years, our team had become so dialed-in (we averaged 99% of asking price received and closed 90%+ of engagements in an industry where 20–30% is typical), we knew we could back it up. So, the $10,000 guarantee was born: “We’ll value your business and give you a realistic sales price range. We guarantee you’ll get offers from real Buyers within that range in 90 days or less—or we’ll pay you $10,000.” Dealonomy is now the only way to sell your business with an experienced, professional M&A team that runs the process, guarantees results—and does it all for free. You're probably wondering: “How do you make money?” Simple: Buyers happily pay us to solve their biggest pain point—finding a good deal and making it easy to buy it. Right now, it’s ridiculously hard, and they get no love. Most brokers are so fixated on Sellers that Buyers are neglected and treated like they’re a dime a dozen. Buyers feel like they’re searching for a needle in a haystack—sorting through junk and time-wasters, with no one on their side. Dealonomy is basically a Needle Store. No more haystack. The serious Buyers we knew all said they’d happily pay a small percentage fee at closing if we brought them a good deal at a realistic price and saved them a year or more of hassle. So for Buyers, here’s what our platform delivers: - Good Deals Only – Strong earnings. Bankable pricing. Clean financials. Motivated Sellers. - Frictionless Process – A state-of-the-art platform where you can quickly sign NDAs, access fully populated Deal Rooms, make offers, do diligence, and close. - Helpful Advisors – Our Intermediary-Led Process means no more adversarial Brokers. Dealonomy dealmakers work transparently with both sides to find the win/win. The cat’s out of the bag. This is our playbook—and we believe it will transform how Main Street deals get done. We’ve built this deal-facilitation platform by combining: - A no-brainer offer to attract top Sellers at scale - A real solution to the biggest Buyer pain points - Our award-winning Deal Team from Bison Business - Tech leaders with a proven track record of building and scaling products - An Advisory Board and Investor Group of 30+ top minds in M&A - And a pile of capital to hire top talent and invest in tech + marketing to launch it right. Now it’s game on. See you on Dealonomy.
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Had a great call with @theSLRguy this past Thursday. Talked all things business: analysis paralysis, subcontractors, solar & roofing, internal comms, VAs, and of course… data. It’s wild what people are building every day just by grinding and using their resources efficiently. A few months ago, I wouldn’t have imagined hopping on calls with folks from X. Big shoutout to Ryan for taking the time 🙌
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Your culture is determined by what people perceive to be the behaviors you reward and punish. Note: Not what you actually reward and punish, and also not what you say you reward and punish.
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When Kobe Bryant said his insane level of confidence came from knowing he’d done all he could to prepare, it taught me that anytime I’m nervous it means I didn’t prepare enough.
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when bootstrapping from zero to 1, there are a million mouths that come out of the woodworking asking to be fed All in the name of growth … $1500 for local SEO $4500 to wrap your truck $400 for Yelp premium $3500 for a VA headhunter And that’s just SG&A!!! you just don’t need to spend any of it $0 You can just (not) do things Embrace the constraint, and figure out ways to do it for less Here are some creative things we’ve done, YMMV👇🏻 (book is Art of Profitability, inject it into veins)
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Dallas/Fort Worth SMB/ETA meetup: October 22... 5pm-8pm... I expect >100 people to be there. (we had 80 last time) Cohosting this one with the #1 M&A Attorney in Texas - @KHendersonCo I’ve also convinced my friends @JaredJohnsonSBA and @SMBTelecomGuy to pay for everyone’s drinks. And I locked down an AMAZING venue at @BrandonLewin's new comedy club It takes a village to host these events and build a great community. See you soon DFW (emoji salute)🫡 RSVP and event info link below
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All Chipotle needs to do to save its share price is cut seed oils and introduce a breakfast burrito
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