Over the weekend, Kled received a complex multichannel Korean audio task from one of the frontier labs. Within 48 hours, it was live in the Kled app.
We are now sourcing thousands of Korean speakers to produce millions of hours of multichannel audio.
The spec calls for annels, speaker attribution, persistent speaker IDs across recordings, a five-hour capture limit per speaker, 16 kHz+ audio, and documented consent for AI training use.
Available today on iOS: apps.apple.com/us/app/kled/id…
We are now sourcing thousands of Korean speakers to produce millions of hours of multichannel audio.
The spec calls for annels, speaker attribution, persistent speaker IDs across recordings, a five-hour capture limit per speaker, 16 kHz+ audio, and documented consent for AI training use.
Available today on iOS: apps.apple.com/us/app/kled/id…
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the kled marketplace is now live: kled.ai/datasets
labs can request and browse datasets from the kled contributor network and a curated network of enterprise partners.
labs can request and browse datasets from the kled contributor network and a curated network of enterprise partners.
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Introducing Kled Labs.
Every major AI model learned from the internet. We're betting on people instead.
One goal: train our own models to beat closed models at important human tasks, using our data alone.
All data is sourced from our data application layer and our network of We're hiring: jobs.ashbyhq.com/kled-ai/6e94d9…
Every major AI model learned from the internet. We're betting on people instead.
One goal: train our own models to beat closed models at important human tasks, using our data alone.
All data is sourced from our data application layer and our network of We're hiring: jobs.ashbyhq.com/kled-ai/6e94d9…
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The latest version of Kled is available today on the iOS App Store. AI labs looking for structured data can reach out or submit a dataset request at kled.ai/datasets.
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Kled's previous home screen was built around a single upload button for photos already in a contributor's camera roll. Structured tasks lived in a separate tab that most contributors rarely opened.
This meant we could only collect the data people already had, not the data labs places the home screen with a task discovery feed. Every live task is ranked for each contributor, and lab-priority tasks appear first with their pay shown upfront, so the work that matters most to the frontier is what 500,000 contributors see first.
The feed is powered by a recommendation system that learns where each contributor performs best, measured by acceptance rate across modality, task type and region, and personalizes their feed around it. Contributors can also adjust it themselves. Better matching leads to higher acceptance, higher earnings and higher-quality data.
Supply is now programmable. If a lab needs 40,000 minutes of egocentric video from Southeast Asia this week, we route contributors to it directly instead of waiting for the network to produce it.
This meant we could only collect the data people already had, not the data labs places the home screen with a task discovery feed. Every live task is ranked for each contributor, and lab-priority tasks appear first with their pay shown upfront, so the work that matters most to the frontier is what 500,000 contributors see first.
The feed is powered by a recommendation system that learns where each contributor performs best, measured by acceptance rate across modality, task type and region, and personalizes their feed around it. Contributors can also adjust it themselves. Better matching leads to higher acceptance, higher earnings and higher-quality data.
Supply is now programmable. If a lab needs 40,000 minutes of egocentric video from Southeast Asia this week, we route contributors to it directly instead of waiting for the network to produce it.
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Kled FD 1.0, our fraud detection model, is now live across every upload on the platform.
On our internal evaluations, FD 1.0 outperforms the best commercially available systems at detecting duplicate uploads, AI-generated images, content sourced from the internet, edited files a cost per upload basis. Every submission is also scored for task relevance and data quality before it's accepted.
The model is continuously retrained on the fraudulent and low-quality data it catches. It currently identifies and removes 98.4% of bad actors within their first 10 uploads.
On our internal evaluations, FD 1.0 outperforms the best commercially available systems at detecting duplicate uploads, AI-generated images, content sourced from the internet, edited files a cost per upload basis. Every submission is also scored for task relevance and data quality before it's accepted.
The model is continuously retrained on the fraudulent and low-quality data it catches. It currently identifies and removes 98.4% of bad actors within their first 10 uploads.
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Kled V3 supports arbitrary task types across image, video, audio, text and annotation. Examples include egocentric video of someone reorganizing a room, the same object captured from every angle, native conversational speech in rare languages, identifying which images are cting the next button a person would press in an app.
Each task is built from one of 108 templates spanning camera, microphone, screen recording, touch and keyboard input. Every template is fully configurable and includes contributor instructions and reference examples of accepted and rejected submissions.
As a result, any dataset a lab can specify can be built into the app and deployed to 500,000+ contributors within 72 hours, regardless of complexity or modality.
We expect to soon give labs the ability to design and deploy tasks to our contributor network directly using these templates, making the process fully self-serve from request to delivery.
Each task is built from one of 108 templates spanning camera, microphone, screen recording, touch and keyboard input. Every template is fully configurable and includes contributor instructions and reference examples of accepted and rejected submissions.
As a result, any dataset a lab can specify can be built into the app and deployed to 500,000+ contributors within 72 hours, regardless of complexity or modality.
We expect to soon give labs the ability to design and deploy tasks to our contributor network directly using these templates, making the process fully self-serve from request to delivery.
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Over the past year, Kled has grown into the largest consumer data collection network in the world, with more than 500,000 opt-in contributors across the US, Southeast Asia and Europe collecting over 8 million datapoints per day across 38,000 structured datasets.
In working with we found that our existing infrastructure couldn't support many of the complex tasks and modalities needed to advance the frontier.
Eight months ago, we began rebuilding Kled from the ground up. Today, we're releasing the result.
In working with we found that our existing infrastructure couldn't support many of the complex tasks and modalities needed to advance the frontier.
Eight months ago, we began rebuilding Kled from the ground up. Today, we're releasing the result.
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This is Kled V3. We've solved data collection for artificial general intelligence.
Any consumer dataset that can exist, can now be collected from physical reality in under 72 hours.
All powered by the largest and most comprehensive data application layer on the planet. (Thread)
Any consumer dataset that can exist, can now be collected from physical reality in under 72 hours.
All powered by the largest and most comprehensive data application layer on the planet. (Thread)
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Kled has officially crossed 10 million views per week across TikTok, Instagram, and more. Directly from users.
Our app has consistently remained top 100 in 20+ countries and top 10-20 in countries like Indonesia.
Our iPhone market share will soon be supplemented by our new ch just did over 5,000 pre registrations in less than an hour.
Our app has consistently remained top 100 in 20+ countries and top 10-20 in countries like Indonesia.
Our iPhone market share will soon be supplemented by our new ch just did over 5,000 pre registrations in less than an hour.
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We’ve started and are continuing to buy back over $1 million of $KLED in the last 48 hours.
$KLED will ultimately become a fully viable reward currency for our data marketplace and human in the loop fraud detection tools we have built.
As our contracts get bigger and bigger we t our token community accordingly and to our discretion.
$KLED will ultimately become a fully viable reward currency for our data marketplace and human in the loop fraud detection tools we have built.
As our contracts get bigger and bigger we t our token community accordingly and to our discretion.
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Kled has just signed a $12 million non-exclusive data deal over the next 2 years making the marketplace officially profitable.
We’re now heavily expanding our team to bring Kled to android, support every global currency / payment method, increase our daily uploads and by 2x in 1 month, and roll out our next fraud detection model for better data quality.
We want the best engineers in the world. All open careers can be found here: kled.ai
We’re now heavily expanding our team to bring Kled to android, support every global currency / payment method, increase our daily uploads and by 2x in 1 month, and roll out our next fraud detection model for better data quality.
We want the best engineers in the world. All open careers can be found here: kled.ai
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The Data Foundation has invested $3 million into Kled, bringing our total funding to now $14 million.
We’ve been extremely selective with our investors and have only taken strategic capital. The foundation will be joining some of the top venture funds and angels who have all d’s leading human data marketplace.
Kled is on track to do over 5 billion user uploads and have over 2 million daily active data contributors this year. Onwards and upwards.
We’ve been extremely selective with our investors and have only taken strategic capital. The foundation will be joining some of the top venture funds and angels who have all d’s leading human data marketplace.
Kled is on track to do over 5 billion user uploads and have over 2 million daily active data contributors this year. Onwards and upwards.
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Traditional captchas are becoming worthless.
AI can now solve any fixed image grid automatically. reCAPTCHA, hCaptcha, every major service on the market pulls from a pre-labeled problem set. Once AI learns the set, it is over.
UFDP has all the same standard bot detection built elf is unsolvable by AI because it is never the same twice.
Every question is a brand new real world data point pulled live from a pipeline of 5 million daily uploads. There is no problem set to train on. There is no pattern to crack. The only thing that can answer it is a genuine human judgment call.
AI can now solve any fixed image grid automatically. reCAPTCHA, hCaptcha, every major service on the market pulls from a pre-labeled problem set. Once AI learns the set, it is over.
UFDP has all the same standard bot detection built elf is unsolvable by AI because it is never the same twice.
Every question is a brand new real world data point pulled live from a pipeline of 5 million daily uploads. There is no problem set to train on. There is no pattern to crack. The only thing that can answer it is a genuine human judgment call.
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The result on the other end is clean, verified, requirement-perfect data delivered directly to the lab.
The robotics lab gets 10,000 videos. Every single one has both hands visible. Every one filmed in natural daylight. No cuts.
Kled’s sales margin on this data lets us run this ely for free unlike any other service in the market.
The robotics lab gets 10,000 videos. Every single one has both hands visible. Every one filmed in natural daylight. No cuts.
Kled’s sales margin on this data lets us run this ely for free unlike any other service in the market.
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Consensus is everything.
Each question goes to a cluster of at minimum 50 people simultaneously. If 47 say the answer is X and 3 say Y, it is X. The 47 get rewarded. The 3 take a trust score hit, their pay multiplier drops, and they get flagged for closer review.
The network y over time. The best validators earn the most. The bad actors get priced out automatically.
Each question goes to a cluster of at minimum 50 people simultaneously. If 47 say the answer is X and 3 say Y, it is X. The 47 get rewarded. The 3 take a trust score hit, their pay multiplier drops, and they get flagged for closer review.
The network y over time. The best validators earn the most. The bad actors get priced out automatically.
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ufdp.ai is the first free captcha service for any website.
Instead of a standard captcha, users are shown a real anonymized data point pulled exclusively from Kled's pipeline. Install the extension, connect your wallet, and you get paid every time you solve one es the captcha is completely free. For users without the extension it works exactly like a normal captcha, they just don't get paid.
Instead of a standard captcha, users are shown a real anonymized data point pulled exclusively from Kled's pipeline. Install the extension, connect your wallet, and you get paid every time you solve one es the captcha is completely free. For users without the extension it works exactly like a normal captcha, they just don't get paid.
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Kled is the largest opt-in human data marketplace ever built. Over 1 billion data points uploaded to date. Over 5 million new uploads every single day.
Say a robotics lab needs 10,000 videos of someone taking out the trash, both hands visible at all times, filmed in natural that volume, verifying every single upload is impossible. Standard ML fraud models are not good enough to detect that level of requirement complexity at scale. Contributors figure this out fast and start cutting corners.
Say a robotics lab needs 10,000 videos of someone taking out the trash, both hands visible at all times, filmed in natural that volume, verifying every single upload is impossible. Standard ML fraud models are not good enough to detect that level of requirement complexity at scale. Contributors figure this out fast and start cutting corners.
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We created the world’s best captcha.
The first captcha that is: free for companies, pays you to solve it, impossible to bot, and instead of showing you images of random traffic lights, you’re shown real AI training data to validate.
Data is provided exclusively by Kled, and directly to the leading foundation models and robotics companies to further the advancement of AGI.
Introducing ufdp.ai - The Universal Fraud Detection Protocol. (Read Full Thread Below)
The first captcha that is: free for companies, pays you to solve it, impossible to bot, and instead of showing you images of random traffic lights, you’re shown real AI training data to validate.
Data is provided exclusively by Kled, and directly to the leading foundation models and robotics companies to further the advancement of AGI.
Introducing ufdp.ai - The Universal Fraud Detection Protocol. (Read Full Thread Below)
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The first human data marketplace has just crossed over 1 billion uploads.
Tens of thousands of structured and labeled datasets across all human activity.
We are on track to do over 5 billion uploads this year, officially cementing our place as the largest opt in human data story.
This belongs to every person who chose to own their data. Thank you.
Download Kled on the app store today.
Tens of thousands of structured and labeled datasets across all human activity.
We are on track to do over 5 billion uploads this year, officially cementing our place as the largest opt in human data story.
This belongs to every person who chose to own their data. Thank you.
Download Kled on the app store today.
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This group of investors also unlocks hundreds of previously locked doors to some of the leading AI labs, robotics companies, consumer brands, and more, which will allow us to present thousands of new data tasks to the hundreds of thousands of data contributors on the Kled app.
A ther existing investors: Luca Netz (Founder of Pudgy Penguins), 24kGoldn, Abe Burns (Slow Rush Ventures), Adam Cohen (Founder of Stic), Everbloom, Ricky Horwitz (Former CMO of Pika), Magic Labs, A16Z Scout, Bain Scout, Zach Greenberger (Former CBO of Lyft), Max Marchione (Founder of Superpower), Paul Yacoubian (Founder of Copy AI), PandaBoi, and everyone else!
A ther existing investors: Luca Netz (Founder of Pudgy Penguins), 24kGoldn, Abe Burns (Slow Rush Ventures), Adam Cohen (Founder of Stic), Everbloom, Ricky Horwitz (Former CMO of Pika), Magic Labs, A16Z Scout, Bain Scout, Zach Greenberger (Former CBO of Lyft), Max Marchione (Founder of Superpower), Paul Yacoubian (Founder of Copy AI), PandaBoi, and everyone else!
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This raise follows the explosive growth of our consumer app, which has hit number 1 on the app store in 4 countries (Finance Category).
Our users are now uploading anywhere from 3 - 4.5 million files per day. With our top earner making $7,400 per month.
We’ve collected 12,000+ ated spanning egocentric data, medical data (e.g., radiology scans), urban travel data, etc.
Several leading AI labs and enterprises are now actively purchasing our user-generated datasets for frontier model training.
Our users are now uploading anywhere from 3 - 4.5 million files per day. With our top earner making $7,400 per month.
We’ve collected 12,000+ ated spanning egocentric data, medical data (e.g., radiology scans), urban travel data, etc.
Several leading AI labs and enterprises are now actively purchasing our user-generated datasets for frontier model training.
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Today, we’re announcing our $5.5M Seed round to build the first human data marketplace.
Backed by Sebastian Thrun (Founder of Waymo), Aglaé (Venture Fund of Bernard Arnault), K5 Global, Diplo, Parable VC, Cox Exponential (CX2), Daniel Greenberg (Founder of MSCHF), Harrison Shih acob (Owner of Golden State Warriors), and more.
This brings our total financing to $9 million. (Thread)
Backed by Sebastian Thrun (Founder of Waymo), Aglaé (Venture Fund of Bernard Arnault), K5 Global, Diplo, Parable VC, Cox Exponential (CX2), Daniel Greenberg (Founder of MSCHF), Harrison Shih acob (Owner of Golden State Warriors), and more.
This brings our total financing to $9 million. (Thread)
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We've officially broken out of Asia. Kled hit the top of the app store charts in France (#11), Georgia (#19), Canada (#178), Belgium (#49), Pakistan (#33), Cape Verde (#81), Burkina Faso (#80), Nigeria (#79), and Luxembourg (#58) in the last 2 days.
We're one of the fastest countries now.
We're one of the fastest countries now.
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Over $3 million is actively sitting in the wallets of our users. We are rolling out in app notices to swap active payouts to $KLED token for increased payouts starting now.
Kled is now charting top 100 on the App Store in 6 countries and closing in on 200,000 downloads, with ≈ weeks across all posts mentioning the app.
We're on track for 1 million downloads by start of Q2 2026. We're on track to do $100,000,000+ in payouts by start of 2027.
Kled is now charting top 100 on the App Store in 6 countries and closing in on 200,000 downloads, with ≈ weeks across all posts mentioning the app.
We're on track for 1 million downloads by start of Q2 2026. We're on track to do $100,000,000+ in payouts by start of 2027.
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Your Data Your Story. We're excited to announce that Kled is now available in over 170 countries.
Join Mr. Kim and so many more. Take back control over your data: kled.ai/stories.
Join Mr. Kim and so many more. Take back control over your data: kled.ai/stories.
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The wait is over, introducing Kled the first app that lets you upload your personal data and get paid for it.
Fully out of beta and available for everyone on the App Store today. Your data, your story.
Fully out of beta and available for everyone on the App Store today. Your data, your story.
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We’re excited to finally introduce Kled Special Tasks, the final major feature included in the V2 app update.
Users will now have access to a fully interactive terminal where they can view and complete domain specific upload tasks directly from enterprise buyers. These tasks can rson specific. For example, PhD students at Stanford might be prompted to upload their coursework or research materials and get paid for it.
Our first domain specific task will focus on homework collection from high school and college students across Europe and the United States. Students will verify their emails and academic credentials directly within the app. We’ve built labeling workflows to ensure all uploaded content meets our criteria, and participants will receive weighted payouts based on the value of their submissions.
We’ve already built a network of over 3,800 students from Stanford, MIT, UIUC, Rutgers, and Duke who will be actively onboarded to contribute content.
Kled will work hand in hand with our research division, HADES, to justify the large scale purchase of this homework content. Several enterprise buyers have already expressed interest, each confirming that academic data from students represents a growing multi year industry requiring a continuous flow of fresh material.
Kled Special Tasks also gives us the ability to internally identify valuable content types, issue calls for specific datasets, and collect 1,000-2,000 unique samples per task. We can then package these datasets into specialized data packs that our sales team will use to pitch directly to AI labs and enterprise clients with matching data needs. This will be one of our most powerful tools for expanding Kled’s buyer network.
All of this will be fully available in the V2 update. We’re excited to show just how advanced our segmentation and data validation software has become as we bring this release to market.
Users will now have access to a fully interactive terminal where they can view and complete domain specific upload tasks directly from enterprise buyers. These tasks can rson specific. For example, PhD students at Stanford might be prompted to upload their coursework or research materials and get paid for it.
Our first domain specific task will focus on homework collection from high school and college students across Europe and the United States. Students will verify their emails and academic credentials directly within the app. We’ve built labeling workflows to ensure all uploaded content meets our criteria, and participants will receive weighted payouts based on the value of their submissions.
We’ve already built a network of over 3,800 students from Stanford, MIT, UIUC, Rutgers, and Duke who will be actively onboarded to contribute content.
Kled will work hand in hand with our research division, HADES, to justify the large scale purchase of this homework content. Several enterprise buyers have already expressed interest, each confirming that academic data from students represents a growing multi year industry requiring a continuous flow of fresh material.
Kled Special Tasks also gives us the ability to internally identify valuable content types, issue calls for specific datasets, and collect 1,000-2,000 unique samples per task. We can then package these datasets into specialized data packs that our sales team will use to pitch directly to AI labs and enterprise clients with matching data needs. This will be one of our most powerful tools for expanding Kled’s buyer network.
All of this will be fully available in the V2 update. We’re excited to show just how advanced our segmentation and data validation software has become as we bring this release to market.
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We’re launching Kled HADES: The Human Aligned Data Evaluation Standard.
As Kled has matured, we’ve realized something the AI industry still hasn’t addressed. The world’s most advanced models are being evaluated on synthetic, filtered, or scraped data that doesn’t reflect real rform well on benchmarks that exist in theory but collapse when faced with the entropy of the real world.
Mercor’s APEX measures how well models perform economically valuable work across consulting, law, and medicine. Kled HADES, by contrast, measures how well those same models perform when exposed to real human data.
For example, a model might summarize a clean academic paper perfectly, but fail when given a real student’s PhD thesis draft full of comments, formatting errors, handwriting, and half finished equations. HADES tests models on that kind of reality, the raw, unfiltered data that defines how people actually create and communicate.
Those failures are not a labeling problem. They are a distribution problem. Models fail because they have never been exposed to this kind of authentic, human data during training. The world they were taught to understand is synthetic. The world they are being deployed into is not.
That is where Kled comes in. The data we collect through our platform reflects the real world in all its complexity: videos, documents, conversations, behavioral data, and sensory recordings, all verified and sourced from real people. When AI labs integrate this data into training and evaluation, models become more robust, grounded, and aligned with reality.
To make HADES truly representative, we’ve partnered with experts across disciplines to construct domain specific evaluation rubrics. With partners at Latham & Watkins, engineers from over 20 Fortune 500 companies, five Grammy nominated artists, six Division I athletic coaches, and ten decorated medical professionals, we’re designing tests that expose where models fail to interpret the data real people produce.
Where Mercor uses experts to measure task performance and close the gap with more labor, Kled uses experts to measure data comprehension and close the gap with better data. HADES doesn’t evaluate what a model can output. It evaluates whether the model can even understand the inputs humans generate every day.
We’ve assembled a dedicated research team to design the evaluation sets, metrics, and scoring frameworks that will form the foundation of HADES and define what true alignment with human data looks like.
We will use HADES to evaluate and rank the top models from every major AI lab on how well they understand authentic human data. The insights we uncover will guide where the industry’s data needs to evolve and position Kled as the primary source for closing those gaps.
This benchmark is more than research. It is one of the most important steps in increasing the scale, defensibility, and value of Kled’s ecosystem. It also marks the second to last piece of the puzzle before our full company update.
We’re hiring. If you’re an AI researcher who wants to help define this new standard and work alongside top talent from Stanford SAIL, email: team@kled.ai.
As Kled has matured, we’ve realized something the AI industry still hasn’t addressed. The world’s most advanced models are being evaluated on synthetic, filtered, or scraped data that doesn’t reflect real rform well on benchmarks that exist in theory but collapse when faced with the entropy of the real world.
Mercor’s APEX measures how well models perform economically valuable work across consulting, law, and medicine. Kled HADES, by contrast, measures how well those same models perform when exposed to real human data.
For example, a model might summarize a clean academic paper perfectly, but fail when given a real student’s PhD thesis draft full of comments, formatting errors, handwriting, and half finished equations. HADES tests models on that kind of reality, the raw, unfiltered data that defines how people actually create and communicate.
Those failures are not a labeling problem. They are a distribution problem. Models fail because they have never been exposed to this kind of authentic, human data during training. The world they were taught to understand is synthetic. The world they are being deployed into is not.
That is where Kled comes in. The data we collect through our platform reflects the real world in all its complexity: videos, documents, conversations, behavioral data, and sensory recordings, all verified and sourced from real people. When AI labs integrate this data into training and evaluation, models become more robust, grounded, and aligned with reality.
To make HADES truly representative, we’ve partnered with experts across disciplines to construct domain specific evaluation rubrics. With partners at Latham & Watkins, engineers from over 20 Fortune 500 companies, five Grammy nominated artists, six Division I athletic coaches, and ten decorated medical professionals, we’re designing tests that expose where models fail to interpret the data real people produce.
Where Mercor uses experts to measure task performance and close the gap with more labor, Kled uses experts to measure data comprehension and close the gap with better data. HADES doesn’t evaluate what a model can output. It evaluates whether the model can even understand the inputs humans generate every day.
We’ve assembled a dedicated research team to design the evaluation sets, metrics, and scoring frameworks that will form the foundation of HADES and define what true alignment with human data looks like.
We will use HADES to evaluate and rank the top models from every major AI lab on how well they understand authentic human data. The insights we uncover will guide where the industry’s data needs to evolve and position Kled as the primary source for closing those gaps.
This benchmark is more than research. It is one of the most important steps in increasing the scale, defensibility, and value of Kled’s ecosystem. It also marks the second to last piece of the puzzle before our full company update.
We’re hiring. If you’re an AI researcher who wants to help define this new standard and work alongside top talent from Stanford SAIL, email: team@kled.ai.
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Introducing Kled Enterprise V2. We’ve officially migrated the majority of all of our enterprise contracts to not only include past catalogs but now future catalogs in their possessions.
In other words Kled’s content library from some of the biggest holdings companies, orgs, rows along side theirs.
After this migration we have added over 300 titles, with tens of thousands of pieces of content coming our way progressively every day, month and year.
Titles include: Al Capone, Fury, Mighty Mouse, Star Trek: The Animated Series, Atomic Train, Death Valley Days, Casper the Friendly Ghost, etc. We’ve attached a more complete list of content that was recently added as a result of our contract format to this thread.
This new structure perfectly aligns with our vision that: companies should keep focusing on what they do best, creating great content or acquiring great content, while Kled focuses on what we do best, finding new ways to monetize their catalogs for the age of artificial intelligence.
In other words Kled’s content library from some of the biggest holdings companies, orgs, rows along side theirs.
After this migration we have added over 300 titles, with tens of thousands of pieces of content coming our way progressively every day, month and year.
Titles include: Al Capone, Fury, Mighty Mouse, Star Trek: The Animated Series, Atomic Train, Death Valley Days, Casper the Friendly Ghost, etc. We’ve attached a more complete list of content that was recently added as a result of our contract format to this thread.
This new structure perfectly aligns with our vision that: companies should keep focusing on what they do best, creating great content or acquiring great content, while Kled focuses on what we do best, finding new ways to monetize their catalogs for the age of artificial intelligence.
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Introducing Kled ROS. The future of data collection for robotics.
For the past three months, Kled has been building the most advanced infrastructure for robotic perception, from top tier data collection systems to intuitive labeling interfaces.
We’re now expanding into one of ic data collection categories: household and daily life robotics tasks, filmed by everyday Americans.
Kled has allocated $150,000 toward purchasing cutting edge visual equipment such as Meta Glasses, GoPros, and wearable 4K sensors, which will be shipped to thousands of middle income Americans who have agreed to record their daily household routines.
Another $150,000 has been allocated directly to rewarding participants for their contributions.
After months of small scale testing, we now have the full production infrastructure ready, enabling large scale robotic training data collection at an unprecedented level of realism.
Our team of engineers is currently finalizing action labeling interfaces that break down each task, including washing dishes, taking out the trash, making the bed, vacuuming, and cooking, into repeatable programmable sequences, turning every action into structured code readable events.
Kled will also be co sponsoring multiple upcoming events with leading Silicon Valley robotics companies throughout the next two months.
Stay tuned, this is just the beginning of Kled ROS.
For the past three months, Kled has been building the most advanced infrastructure for robotic perception, from top tier data collection systems to intuitive labeling interfaces.
We’re now expanding into one of ic data collection categories: household and daily life robotics tasks, filmed by everyday Americans.
Kled has allocated $150,000 toward purchasing cutting edge visual equipment such as Meta Glasses, GoPros, and wearable 4K sensors, which will be shipped to thousands of middle income Americans who have agreed to record their daily household routines.
Another $150,000 has been allocated directly to rewarding participants for their contributions.
After months of small scale testing, we now have the full production infrastructure ready, enabling large scale robotic training data collection at an unprecedented level of realism.
Our team of engineers is currently finalizing action labeling interfaces that break down each task, including washing dishes, taking out the trash, making the bed, vacuuming, and cooking, into repeatable programmable sequences, turning every action into structured code readable events.
Kled will also be co sponsoring multiple upcoming events with leading Silicon Valley robotics companies throughout the next two months.
Stay tuned, this is just the beginning of Kled ROS.
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Introducing Kled Labeling, the next major update of the Kled app.
For the first time, everyday people can earn real income from AI’s fastest growing sector: data labeling.
Users now have the ability to label content in the most intuitive way possible from the hottest , with millions of dollars allocated in rewards.
So whether you're on your couch watching TV, at the dinner table, in bed, anywhere you can earn just with the tap of a button.
We’re not hiring VAs. We’re not outsourcing overseas.
We’re building a collective of users to outpace the billion dollar giants like Mercor, Scale AI, Surge, and more.
This is the first public application that lets anyone earn by labeling data. Every American and global citizen will become the network.
This is the first public application that lets anyone earn by labeling data. Every American and global citizen will become the network.
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We’re thrilled to announce that Kled has signed an exclusive AI licensing agreement with its first government organization, Maryland Public Television (MPT), one of the largest statewide networks in the Public Broadcasting Service (PBS) family.
For over 50 years, MPT has been e most decorated regional broadcasters in America, earning 211 Capital Emmy® Awards from the National Academy of Television Arts & Sciences, along with multiple national Emmys and the Board of Governors Award for overall excellence.
Under this deal, Kled now holds one of the most versatile TV catalogues across crime, science, nature, and local storytelling. Hundreds of broadcast shows are now converting to high fidelity training data.
This is historically one of the first and largest TV publishing deals specifically for AI training. We’re beyond excited to continue to push these boundaries and sign the biggest production networks in the world.
This is premium, authorized training data. If labs want to train on it legally, they now come through Kled.
This is just the start, more and more government organizations will continue to trust Kled with their data. Welcome to the family MPT.
For over 50 years, MPT has been e most decorated regional broadcasters in America, earning 211 Capital Emmy® Awards from the National Academy of Television Arts & Sciences, along with multiple national Emmys and the Board of Governors Award for overall excellence.
Under this deal, Kled now holds one of the most versatile TV catalogues across crime, science, nature, and local storytelling. Hundreds of broadcast shows are now converting to high fidelity training data.
This is historically one of the first and largest TV publishing deals specifically for AI training. We’re beyond excited to continue to push these boundaries and sign the biggest production networks in the world.
This is premium, authorized training data. If labs want to train on it legally, they now come through Kled.
This is just the start, more and more government organizations will continue to trust Kled with their data. Welcome to the family MPT.
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Kled now holds the exclusive AI licensing rights to over 30,000 pieces of entertainment, including Bugs Bunny, Woody Woodpecker, Tennessee Tuxedo, Tom & Jerry, Pink Panther, Popeye, The Twilight Zone, Garfield, and thousands more classics.
This deal 6 months in the making, signja Digital Holdings, marks one of the largest cartoon and TV catalog partnerships in AI history.
For decades, these titles built the foundation of modern animation. Now they will power the next generation of artificial intelligence.
AI companies have been training on this data for years without permission. From now on, if they want to legally train on it, they have to come through Kled.
This deal 6 months in the making, signja Digital Holdings, marks one of the largest cartoon and TV catalog partnerships in AI history.
For decades, these titles built the foundation of modern animation. Now they will power the next generation of artificial intelligence.
AI companies have been training on this data for years without permission. From now on, if they want to legally train on it, they have to come through Kled.
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