“There’s nothing artificial about AI. It’s inspired by people, it’s created by people…” – Fei-Fei Li
❓ What You’ll Learn
- How did a call-recording app hit #2 on the App Store and go dark the next day?
- How much can a dying startup get for its Slack messages and code?
- Who pays poets $150 an hour to grade AI?
- Why are labs paying for calls and chores they cannot scrape from the public web?
- Why did a robot company spend $15 million in one year on home chore video?
- Why can a delivery or ride app turn millions of couriers into data collectors overnight?
- Where are AI labs paying four dollars a minute for footage creators never published?
- Why are some data apps moving from one-time payouts to revenue sharing with contributors?
💎 Why It Matters
Apps now pay for data that AI labs can’t find.
🔍 Problem
Frontier labs have already trained on most of the public web.
The data they need next sits on your phone and inside private companies.
💡 Solution
Apps pay for your calls, photos and videos, then sell them to AI labs.
🏁 Players
Apps That Pay for Your Data
- Kled • Pays for photos, videos and lab-ordered tasks.
- Silencio • Pays for voice recordings in local languages.
- Neon • Dialer that pays you to record calls.
AI Trainer Platforms
- Mercor • Doctors, lawyers and bankers grading model output.
- DataAnnotation • Expert network for paid writing and coding tasks.
- micro1 • AI recruiter staffing lab and robot data work.
Company Data Marketplaces
- SimpleClosure • Sells closing startups’ code and workspace data.
- Mercor • Licenses companies’ Slack, email and code to labs.
- Sunset • Wind-down firm reselling client data through Replay.
Microtask Apps
- Figure Index • Pays people to film household chores.
- DoorDash Tasks • Couriers paid to film chores and record speech.
- Uber AI Solutions • Paid data tasks inside the Uber Driver app.
🔮 Predictions
- Robot makers will pay people to film chores at home.
- Figure has paid $15M to people filming chores.
- micro1 hired thousands of workers in 50+ countries to film laundry, dishes and cooking.
- Gig apps will pay workers to collect AI data between jobs.
- DoorDash launched a Tasks app that pays couriers to film chores and record speech.
- Uber piloted paid data tasks for drivers in 12 Indian cities.
- Voice apps will pay extra for recordings in languages AI models handle badly.
- Indigenius pays a 50% bonus for under-represented languages.
- Babel Audio focuses on English conversation, so rarer languages stay scarce.
☁️ Opportunities
- Build a network of experts who grade AI answers for one profession.
- Mercor passed $2B gross annualized revenue.
- Mercor pays poets $150 an hour to grade verse.
- Surge AI made $1.2B in 2024 with no outside funding.
- Start a review site that ranks which data apps and AI trainer gigs actually pay.
- RemoWork publishes guides to chore-filming apps.
- AI Training Jobs Finder reviews single AI-training platforms.
- Test each app’s payouts yourself and update the rankings monthly.
- Help companies license their tickets, docs and code to AI labs each year.
- micro1 pays $100,000+ for an enterprise data partnership with a company.
- Turing’s Project Lazarus buys records up to $1M.
- A company that shuts down sells its tickets, docs and code once. One that keeps running can license them each year.
🏔️ Risks
- Consent Lawsuits • Record only people who agreed, since one-sided recording already drew a class action.
- Store Removal • Expect app-store crackdowns on apps that pay for home bandwidth or sensitive recordings, since Google disables residential proxy apps that pay users that way.
🔑 Key Lessons
- Chase the rare data. People earn a few dollars a month sharing bandwidth and experts earn up to $150 an hour grading AI answers.
- Get proof of consent. Labs pay more for data they can show people agreed to share.
🔥 Hot Takes
- The public web was the free sample. Labs now pay for what it lacked.
- Labs call it theft when someone copies them. Anthropic trained Claude on pirated books, then accused labs of copying Claude.
😠 Haters
“You’re selling your voice forever.”
Once a model trains on your voice, that sale is permanent. You can’t untrain a model on your voice; you only control what you sell next time. Sell only recordings you’d sell forever and prefer apps that keep paying. Indigenius shares 30% of model revenue with contributors.
“The pay is pennies.”
Thousands of people can supply common data, so apps pay the lowest price someone will accept. Sell the data few people can supply.
“Selling your old team’s Slack is selling your employees’ private lives.”
Leave out direct messages, HR, pay and client data, since the flight attendants’ union objected on privacy grounds when Spirit Airlines sold staff messages.
“Labs will switch to synthetic data and stop paying people.”
Synthetic data will cut what labs pay for easy-to-fake data. Robot simulators still learn from real footage, so sell that. Robot maker Figure paid $15M for chore videos in a year.
🔗 Links
- Will We Run Out of Data? • When the public text AI trains on runs out.
- Would You Share Your Phone Calls With a Company to Make Money? This Startup Is Banking on It • How Neon’s founder rebuilt the app after the breach and what experts think of paying for call data.
- Meta Enters AI Licensing Fray, Striking Deals With People Inc., USA Today Co. and More • Why labs and platforms still pay publishers for training access when the free-web era ends.
- Subterranean Moderators • The pay-per-task labor model data-for-cash apps inherit from older crowdsourcing.
📈 What else?
Trends PRO #0187: Data-for-Cash Apps has more insights.
What you’ll get:
- 45 Players (275% more)
- 8 Predictions (167% more)
- 10 Opportunities (233% more)
- 4 Risks (100% more)
- 4 Key Lessons (100% more)
- 4 Hot Takes (100% more)
- 8 Links (100% more)
With Trends Pro you’ll learn:
- (📈 Pro) Which camera maker offered owners $2 per video?
- (📈 Pro) Which app paid $0.30 a minute for calls between 2 of its users?
- (📈 Pro) Which voice app pays a 50% bonus for some languages?
- (📈 Pro) Which payout route costs bandwidth sharers 15% of each withdrawal?
- (📈 Pro) Which data pool drew 1.3M users before it launched?
- (📈 Pro) Why did customers leave a data vendor after Meta bought nearly half of it?
- And much more…
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