This startup bets India’s gig workers will train global robots

In recent years, India’s online food delivery ecosystem has exploded, with Zomato and Swiggy both going public and cloud kitchens multiplying rapidly. Parallel to this, home services platforms like Urban Company, Snabbit, and Pronto have carved out a growing niche for on-demand household staffing. Now, a Silicon Valley startup called Human Archive is capitalizing on this momentum by partnering with such companies to equip workers with camera-equipped caps that capture egocentric (first-person) video data of routine tasks , footage that could one day train robots to perform similar work.

While the startup has not disclosed its partners by name, it confirms collaborations with firms in the home services, hotel, and restaurant sectors to collect this first-person perspective data. Human Archive reports that it currently has over 1,000 active headsets deployed across multiple locations.

Building on this traction, the company announced on Tuesday that it has secured $8.2 million in funding from Wing Venture Capital, NVP Capital, Y Combinator, and angel investors affiliated with OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, and Meta.

The founding team comprises four students , three from UC Berkeley and one from Stanford: Samay Maini, Rushil Agarwal, Shloke Patel, and Raj Patel (the latter two are cousins, with Raj serving as CEO). All four bring research backgrounds spanning robotics, hardware, and tactile data.

Human Archive’s founding thesis is a direct bet on the trajectory of the AI industry. As robotics labs and frontier AI companies race to build machines capable of physical real-world tasks, they face a critical bottleneck: a shortage of high-quality, real-world training data showing humans performing everyday work. The startup’s core bet is that the workers powering India’s booming gig economy represent an untapped, scalable source of exactly that data.

Although Human Archive has secured some partnerships, it has also faced rejection from major Indian home services companies, including Pronto and Urban Company. This rejection became public last weekend when Indian outlet Entrackr reported that Pronto is actively seeking similar robotics training data partnerships, and that Snabbit had held early talks with Human Archive before the deal collapsed.

Urban Company CEO Abhiraj Singh Bhal responded on X, stating the company would not engage in such arrangements. Patel fired back, warning that Urban Company would soon be forced to reconsider or risk losing relevance to customer churn. Co-founder Rushil Agarwal was even more blunt, posting that Pronto founder Anjali Sardana had laughed at him and called him “stupid” when he proposed a data partnership. Pronto acknowledged the discussions but said it chose not to proceed.

Across India, other startups are collecting egocentric data from environments like factory floors. To differentiate itself, Human Archive is developing and deploying additional devices, including tactile gloves, a full-body motion capture suit, and wrist cameras that capture motion and tactile force data, synchronized in real time with RGB-D (color imagery paired with depth information). The startup believes video data alone is insufficient, but pairing it with other sensor data dramatically increases its value.

Initially, Human Archive relied on makeshift setups or off-the-shelf rigs. Now it is building custom hardware designed to work together and capture multiple data types. The company already has more than 50 different devices deployed to collect varied 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 explained in a call.

The company is also developing ways to fine-tune AI models using its own data and test them on robots to evaluate task effectiveness. This approach allows Human Archive to demonstrate data quality to potential customers and post-train internal models.

Zach DeWitt, a partner at Wing VC, noted that the startup holds a unique advantage in collecting data from multiple sensors simultaneously.

“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.

Despite rejection from prominent home services players, Human Archive has teamed up with smaller startups to offer discounted services to customers. When a worker arrives at a home, consumers choose through the app: pay a discounted price in exchange for consenting to data collection, or pay the full price for an unrecorded visit. Patel said customers have been happy to opt for the former, as video recordings can help resolve disputes about service quality.

The company pays workers a base rate of $1 per hour for participating in egocentric data collection. For context, a report from the Economic Times indicates other companies pay between ₹250 and ₹400 per hour (roughly $2.63 to $4.20). Patel acknowledged that competitors pay more, but said Human Archive’s 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 added.

Beyond wages, privacy concerns around video data collection remain. It is unclear what information Human Archive gives workers about how their footage is used. The company says its commercial contracts comply with India’s Digital Personal Data Protection (DPDP) Act, displaying a privacy policy notice and consent information detailing the purpose of data collection and processing. All data is anonymized, and faces are blurred from recordings. Last week, Moneycontrol reported that India’s Ministry of Electronics and Information Technology is investigating the consent mechanisms and data-collection practices of startups collecting egocentric data through home service workers.

While Human Archive currently collects data largely in India, it has begun 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 plans to offer U. S. customers services like cleaning or cooking in exchange for data collection by participating workers, though these programs are still in early pilot stages.

Multiple well-funded startups are now racing to build physical AI, which requires massive amounts of training data showing humans at work. Human Archive is competing to serve that demand. Whether its approach can scale will depend on the partnerships it secures and the uniqueness and volume of the data it can collect to satisfy the appetite of physical AI labs.