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Human Archive AI builds the infrastructure needed for large-scale deployment of humanoid robots. It creates the underlying software and systems that connect, manage, and coordinate robot fleets so humans can shift from physical labor to more creative work. The company focuses on the infrastructure layer, providing the foundations other firms need to deploy and integrate humanoid robots at scale, rather than selling a single hardware product. This approach helps organizations orchestrate robotics software, data, and AI across multiple robots and environments. Compared to competitors, Human Archive AI differentiates itself by concentrating on scalable, enterprise-ready infrastructure for robotic deployment and workforce transformation, rather than on individual robots or point solutions. The goal is to accelerate the transition of the labor market driven by advanced robotics, enabling a future where humanoid workers augment human creativity and productivity across industries.
Industries
Robotics & Automation
Industrial & Manufacturing
Enterprise Software
AI & Machine Learning
Company Size
11-50
Company Stage
Seed
Total Funding
$8.3M
Headquarters
San Francisco, California
Founded
2025
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Total Funding
$8.3M
Above
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Funded Over
2 Rounds
Industry standards
Remote Work Options
Human Archive, a startup founded by Stanford and UC Berkeley researchers, has raised $8.2 million in seed funding led by Wing Venture Capital to create robot training data using India's gig workers. The round included NVP Capital, Y Combinator and angel investors from OpenAI, Nvidia, Google and Meta. The company equips home services and delivery workers with head-mounted cameras and sensors to capture first-person video of everyday tasks. It has deployed over 1,000 headset units across partner companies, collecting synchronised RGB-D video, tactile force and motion capture data. Workers receive approximately $1 per hour, lower than competitors' rates. Human Archive faces regulatory scrutiny from India's Ministry of Electronics and Information Technology over consent mechanisms and data protection compliance. The startup is expanding to Southeast Asia and the United States.
Human Archive, a Silicon Valley startup, has raised $8.2 million from Wing Venture Capital, NVP Capital, Y Combinator and angels from OpenAI, Nvidia and Google. The company partners with Indian gig economy firms to equip workers with camera-equipped caps to collect first-person video data for training robots. Founded by four Berkeley and Stanford students, Human Archive has deployed over 1,000 headsets across home services, hospitality and restaurant sectors. The startup uses multiple sensors including tactile gloves, motion capture suits and wrist cameras to capture synchronized data beyond simple video footage. The company pays workers $1 per hour for data collection and offers customers discounted services in exchange for consent. However, it faces privacy concerns and regulatory scrutiny from India's Ministry of Electronics, alongside rejections from major platforms including Urban Company and Pronto.
Human Archive's ai-powered caps turn gig workers into street-level data collectors. In recent years, India's online food delivery sector has experienced remarkable growth, with major players like Zomato and Swiggy going public and a surge in cloud kitchens. At the same time, home service platforms - such as Urban Company, Snabbit, and Pronto - have gained traction among consumers seeking on-demand household help. Tapping into this momentum, Silicon Valley-based startup Human Archive is partnering with these companies to equip workers with special caps fitted with cameras. These cameras capture egocentric, or first-person, video footage of everyday tasks, which can then be used to train robots. While the startup hasn't disclosed specific partners, it says it collaborates with companies in home services, hostels, and restaurants to collect this data, boasting over 1,000 active headsets deployed across multiple locations. Building on this early traction, Human Archive announced Tuesday that it has secured $8.2 million in funding from Wing Venture Capital, NVP Capital, Y Combinator, and angel investors from OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, and Meta. The startup was founded by two Berkeley and two Stanford students - Samay Mani, Rushil Agarwal, Shloke Patel, and Raj Patel (the latter two are cousins) - all with research backgrounds in robotics, hardware, and tactile data. The company's creation 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 at work. Human Archive's bet is that workers in India's booming gig economy represent an untapped and scalable source of exactly that data. Although Human Archive works with multiple partners, the startup revealed that it was rejected by several Indian home services companies, including Pronto and Urban Company, for collaboration. This rejection 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. 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 insufficient, but pairing it with other sensor data makes it significantly more valuable. The founders began talking to different labs and realized that the market for egocentric and sensor-based data was just heating up, so they decided to build a company around that. Initially, Human Archive used makeshift setups or off-the-shelf rigs to capture 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," a co-founder said in a call. The company says 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, noted that 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. 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. Raj 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-₹400 per hour (roughly $2.63-$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 says 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 says 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.
Human Archive innovates in Data Collection for AI with egocentric data from Indian gig economy. The Silicon Valley startup Human Archive is gaining traction by collecting egocentric data - videos from the first-person perspective - using wearable camera-equipped caps. Their goal is to obtain high-quality training datasets for robotic AI. * Key Players: Human Archive, founded by Samay Maini, Rushil Agarwal, Shloke Patel, and Raj Patel from UC Berkeley and Stanford, is spearheading this initiative with a background in AI and robotics. * Funding and Partners: The startup has raised $8.2 million, backed by investors like Wing Venture Capital and Y Combinator. Despite being rejected by major Indian companies like Pronto and Urban Company, they've partnered with smaller startups to incentivize data collection during home service visits. * Data Collection and Usage: Human Archive is pioneering in synchronizing multiple sensor data types, including full-body motion capture and RGB-D imagery, to offer comprehensive datasets. These efforts target resolving challenges in robotics AI which demands diverse and rich human activity data. * Market Trends and Challenges: As India and Southeast Asia thrive in the gig economy, the approach taps into this growth, although it faces obstacles such as data privacy and partnership rejections. The firm ensures compliance with India's Digital Personal Data Protection (DPDP) Act to address privacy concerns. * Expansion Plans: While primarily operating in India, Human Archive is already expanding into Southeast Asia and the U.S., aiming to establish an international network of data-collecting partners. CEO Abhiraj Singh Bhal of Urban Company and Pronto founder Anjali Sardana have publicly discussed data partnerships, which adds a layer of public discourse and positioning in the competitive field of physical AI.
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Industries
Robotics & Automation
Industrial & Manufacturing
Enterprise Software
AI & Machine Learning
Company Size
11-50
Company Stage
Seed
Total Funding
$8.3M
Headquarters
San Francisco, California
Founded
2025
Find jobs on Simplify and start your career today