This Startup Is Betting India's Gig Economy Can Train the World's Robots
2026-05-27 00:00·37天前·Ivan Mehta
AI 摘要
由伯克利和斯坦福研究人员创立的初创公司 Human Archive，正在印度支付零工工人工资，让他们佩戴装有摄像头的帽子和传感器设备，以收集 AI 和机器人实验室竞相获取的现实世界物理训练数据。
原文 · 未翻译
In the last few years, India’s online food delivery market has grown significantly, with both Zomato and Swiggy going public and the number of cloud kitchens increasing. Meanwhile, startups working on home services, such as on-demand household staffing platforms like Urban Company, Snabbit, and Pronto, have gained popularity.
Silicon Valley-based startup Human Archive is tapping into this trend, partnering with these companies to have workers wear special caps with cameras to collect egocentric (first-person point of view) video data of everyday tasks that could be used to train robots.
Without naming specific partners, the startup said it is working with companies in the home services, hotel, and restaurant sectors to collect egocentric data, and it says it has more than 1,000 active headsets deployed across multiple locations.
On the back of that traction, Human Archive said Tuesday it has raised $8.2 million in funding from Wing Venture Capital, NVP Capital, Y Combinator, and angels from OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, and Meta.
The startup was founded by three students from UC Berkeley and one from Stanford — Samay Maini, Rushil Agarwal, Shloke Patel, and Raj Patel, the latter two being cousins. (Raj Patel is CEO.) All four have research backgrounds spanning robotics, hardware, and tactile data.
The company’s founding is a direct bet on where the AI industry is heading. As robotics labs and frontier AI companies race to build machines that can perform physical tasks in the real world, they face a critical bottleneck — a shortage of high-quality, real-world training data showing humans doing everyday work. Human Archive’s bet is that the workers staffing India’s booming gig economy represent an untapped and scalable source of exactly that data.
While Human Archive is working with multiple partners, the startup said it was rejected by many Indian home services companies, including Pronto and Urban Company, for a collaboration.
The company’s rejection by major players became public fodder last weekend, when Indian outlet Entrackr reported that Pronto is actively seeking partnerships to collect worker data for robotics training and that Snabbit had held early discussions with Human Archive before the project fell apart.
由伯克利和斯坦福研究人员创立的初创公司 Human Archive，正在印度支付零工工人工资，让他们佩戴装有摄像头的帽子和传感器设备，以收集 AI 和机器人实验室竞相获取的现实世界物理训练数据。
原文 · 保持原样，未翻译
In the last few years, India’s online food delivery market has grown significantly, with both Zomato and Swiggy going public and the number of cloud kitchens increasing. Meanwhile, startups working on home services, such as on-demand household staffing platforms like Urban Company, Snabbit, and Pronto, have gained popularity.
Silicon Valley-based startup Human Archive is tapping into this trend, partnering with these companies to have workers wear special caps with cameras to collect egocentric (first-person point of view) video data of everyday tasks that could be used to train robots.
Without naming specific partners, the startup said it is working with companies in the home services, hotel, and restaurant sectors to collect egocentric data, and it says it has more than 1,000 active headsets deployed across multiple locations.
Urban Company CEO Abhiraj Singh Bhal responded on X, stating the company would not engage in such arrangements — prompting Patel to fire back that Urban Company would soon be forced to reconsider or risk losing relevance to customer churn. Co-founder Rushil Agarwal was blunter still, posting that Pronto founder Anjali Sardana had laughed at him and called him “stupid” when he raised the idea of a data partnership. Pronto acknowledged the conversations, but said it chose not to move forward. The startup denied calling Agarwal “stupid.”
Across the country, other startups are collecting egocentric data from different work environments, including factory floors. To differentiate itself, Human Archive is using and developing additional devices, such as tactile gloves, a full-body motion capture suit, and wrist cameras to capture data, including motion and tactile force, synchronously aligned with RGB-D (color imagery paired in real time with depth information), to sell to AI labs. The startup believes that video data alone is not sufficient but that pairing it with other sensor data makes it much more valuable.
Initially, Human Archive used makeshift setups or off-the-shelf rigs to capture the data. Now it is working on custom hardware that works together and captures different kinds of data. It already has more than 50 different devices deployed to collect different data points.
“To capture data, we started with iPhones; then we built our own custom rigs and caps. Now we have more than seven different hardware products that we use interchangeably across different modalities. After data collection from different devices, we worked on synchronizing data from all these different sources,” Patel said in a call.
The company said it is developing ways to fine-tune AI models with its own data and test them on robots to evaluate task effectiveness. By doing this, the startup can demonstrate the quality of its data to potential customers and post-train internal models.
Zach DeWitt, a partner at Wing VC, said the startup has a unique advantage in collecting data from multiple sensors.
“No one else in the world has been able to synchronize and collect headset RGB-D, force feedback, full-body motion capture, and synchronized chest and wrist camera data at scale. They’ve been doing internal model training on this data, and every major lab and university is interested in running experiments on it due to the novelty of the sensors and the scale of the new dataset they are releasing soon,” he told TechCrunch.
Collecting data in India and expansion plans
Despite rejection from notable players in the home services industry, Human Archive teamed up with smaller startups to offer discounted services to customers. When a worker arrives at a home, consumers are offered a choice through the app: pay a discounted price in exchange for consenting to data collection, or pay the full price for an unrecorded visit.
Patel mentioned that customers have been happy to opt for the former, as disputes about service quality are common, and video recordings can help resolve them.
The company pays workers a base rate of $1 per hour for participating in egocentric data collection. A report from the Economic Times suggests that other companies pay ₹250 to ₹400 per hour (roughly $2.63 to $4.20). Patel said competitors pay more than Human Archive, but its on-the-ground presence in India allows it to keep compensation lower.
“Human Archive’s network provides immediate, flexible earning opportunities globally, lowering the barrier to participating in the AI economy. We see this as a critical bridge that funds immediate livelihoods while building the infrastructure for a safer, more productive future,” DeWitt said.
Beyond wage payment, there are privacy concerns around data collection via video recording. It is not clear what information Human Archive gives workers about how their footage is used. The company said that its commercial contracts are compliant with India’s Digital Personal Data Protection (DPDP) Act, as it displays a privacy policy notice, along with consent information detailing the purpose of data collection and how it is processed. The company said all data is anonymized and faces are blurred from recordings. Last week, Moneycontrol reported that India’s Ministry of Electronics and Information Technology is looking into the consent mechanisms and data-collection practices of startups collecting egocentric data through home service workers.
While Human Archive largely collects data in India, it has started expanding into Southeast Asia and the U.S. The company is also building a platform for anyone to participate in data collection and earn money. It also wants to offer customers in the U.S. services like cleaning or cooking in exchange for data collection by participating workers — though these programs are just in an early pilot stage.
Multiple well-funded startups are racing to build physical AI. Doing so requires massive amounts of training data showing humans at work — and Human Archive is one of the players competing to serve that demand. Whether its approach can scale will hinge on the partnerships it strikes and the uniqueness and volume of the data it can collect to satisfy the appetite of physical AI labs.
On the back of that traction, Human Archive said Tuesday it has raised $8.2 million in funding from Wing Venture Capital, NVP Capital, Y Combinator, and angels from OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, and Meta.
The startup was founded by three students from UC Berkeley and one from Stanford — Samay Maini, Rushil Agarwal, Shloke Patel, and Raj Patel, the latter two being cousins. (Raj Patel is CEO.) All four have research backgrounds spanning robotics, hardware, and tactile data.
The company’s founding is a direct bet on where the AI industry is heading. As robotics labs and frontier AI companies race to build machines that can perform physical tasks in the real world, they face a critical bottleneck — a shortage of high-quality, real-world training data showing humans doing everyday work. Human Archive’s bet is that the workers staffing India’s booming gig economy represent an untapped and scalable source of exactly that data.
While Human Archive is working with multiple partners, the startup said it was rejected by many Indian home services companies, including Pronto and Urban Company, for a collaboration.
The company’s rejection by major players became public fodder last weekend, when Indian outlet Entrackr reported that Pronto is actively seeking partnerships to collect worker data for robotics training and that Snabbit had held early discussions with Human Archive before the project fell apart.
Urban Company CEO Abhiraj Singh Bhal responded on X, stating the company would not engage in such arrangements — prompting Patel to fire back that Urban Company would soon be forced to reconsider or risk losing relevance to customer churn. Co-founder Rushil Agarwal was blunter still, posting that Pronto founder Anjali Sardana had laughed at him and called him “stupid” when he raised the idea of a data partnership. Pronto acknowledged the conversations, but said it chose not to move forward. The startup denied calling Agarwal “stupid.”
Across the country, other startups are collecting egocentric data from different work environments, including factory floors. To differentiate itself, Human Archive is using and developing additional devices, such as tactile gloves, a full-body motion capture suit, and wrist cameras to capture data, including motion and tactile force, synchronously aligned with RGB-D (color imagery paired in real time with depth information), to sell to AI labs. The startup believes that video data alone is not sufficient but that pairing it with other sensor data makes it much more valuable.
Initially, Human Archive used makeshift setups or off-the-shelf rigs to capture the data. Now it is working on custom hardware that works together and captures different kinds of data. It already has more than 50 different devices deployed to collect different data points.
“To capture data, we started with iPhones; then we built our own custom rigs and caps. Now we have more than seven different hardware products that we use interchangeably across different modalities. After data collection from different devices, we worked on synchronizing data from all these different sources,” Patel said in a call.
The company said it is developing ways to fine-tune AI models with its own data and test them on robots to evaluate task effectiveness. By doing this, the startup can demonstrate the quality of its data to potential customers and post-train internal models.
Zach DeWitt, a partner at Wing VC, said the startup has a unique advantage in collecting data from multiple sensors.
“No one else in the world has been able to synchronize and collect headset RGB-D, force feedback, full-body motion capture, and synchronized chest and wrist camera data at scale. They’ve been doing internal model training on this data, and every major lab and university is interested in running experiments on it due to the novelty of the sensors and the scale of the new dataset they are releasing soon,” he told TechCrunch.
Collecting data in India and expansion plans
Despite rejection from notable players in the home services industry, Human Archive teamed up with smaller startups to offer discounted services to customers. When a worker arrives at a home, consumers are offered a choice through the app: pay a discounted price in exchange for consenting to data collection, or pay the full price for an unrecorded visit.
Patel mentioned that customers have been happy to opt for the former, as disputes about service quality are common, and video recordings can help resolve them.
The company pays workers a base rate of $1 per hour for participating in egocentric data collection. A report from the Economic Times suggests that other companies pay ₹250 to ₹400 per hour (roughly $2.63 to $4.20). Patel said competitors pay more than Human Archive, but its on-the-ground presence in India allows it to keep compensation lower.
“Human Archive’s network provides immediate, flexible earning opportunities globally, lowering the barrier to participating in the AI economy. We see this as a critical bridge that funds immediate livelihoods while building the infrastructure for a safer, more productive future,” DeWitt said.
Beyond wage payment, there are privacy concerns around data collection via video recording. It is not clear what information Human Archive gives workers about how their footage is used. The company said that its commercial contracts are compliant with India’s Digital Personal Data Protection (DPDP) Act, as it displays a privacy policy notice, along with consent information detailing the purpose of data collection and how it is processed. The company said all data is anonymized and faces are blurred from recordings. Last week, Moneycontrol reported that India’s Ministry of Electronics and Information Technology is looking into the consent mechanisms and data-collection practices of startups collecting egocentric data through home service workers.
While Human Archive largely collects data in India, it has started expanding into Southeast Asia and the U.S. The company is also building a platform for anyone to participate in data collection and earn money. It also wants to offer customers in the U.S. services like cleaning or cooking in exchange for data collection by participating workers — though these programs are just in an early pilot stage.
Multiple well-funded startups are racing to build physical AI. Doing so requires massive amounts of training data showing humans at work — and Human Archive is one of the players competing to serve that demand. Whether its approach can scale will hinge on the partnerships it strikes and the uniqueness and volume of the data it can collect to satisfy the appetite of physical AI labs.