미국 실리콘밸리 스타트업 휴먼 아카이브(Human Archive)는 인도 배달 및 가사 서비스 노동자들에게 특수 카메라가 장착된 캡을 씌워 1인칭 관점의 일상 작업 영상 데이터를 수집합니다. 이렇게 확보한 데이터는 로봇 훈련용으로 쓰이며, 기존 영상뿐 아니라 촉각 장갑과 모션 캡처 슈트 등 다양한 맞춤형 하드웨어를 활용해 고품질 멀티 센서 데이터를 생산한다는 점에서 기술적 차별성을 갖습니다. 이 회사는 최근 820만 달러(약 110억 원)의 시드 자금을 유치하며, 실제 물리적 환경을 학습하려는 최첨단 AI 및 로봇 공학 연구소들의 데이터 갈증을 해소해 주는 중요한 역할을 주목받고 있습니다.
번역된 본문
최근 몇 년간 인도의 온라인 음식 배달 시장은 Zomato와 Swiggy가 상장하고 클라우드 키친 수요가 증가하며 급격히 성장했습니다. 이와 동시에 Urban Company, Snabbit, Pronto 등 주문형 가사 서비스 플랫폼을 포함해 가정 내 서비스에 특화된 스타트업들도 큰 인기를 끌고 있습니다. 실리콘밸리에 기반을 둔 스타트업 Human Archive는 이러한 추세에 착안해 이들 기업과 파트너십을 맺고, 작업자들이 카메라가 장착된 특수 캡을 착용하게 하여 로봇 훈련에 사용될 수 있는 일상 작업의 자기중심적(1인칭 관점, egocentric) 비디오 데이터를 수집하고 있습니다. 구체적인 파트너사를 밝히지는 않았으나, 해당 스타트업은 가사 서비스, 호스텔, 레스토랑 분야의 기업들과 협력하여 1인칭 관점 데이터를 수집하고 있으며, 여러 지역에 1,000개 이상의 활성 헤드셋을 배포했다고 밝혔습니다.
이러한 성과를 바탕으로, Human Archive는 화요일에 Wing Venture Capital, NVP Capital, Y Combinator, 그리고 OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, Meta 소속 엔젤 투자자들로부터 820만 달러(약 110억 원)의 자금을 조달했다고 발표했습니다. 이 스타트업은 UC 버클리와 스탠퍼드 대학교 학생 네 명인 Samay Mani, Rushil Agarwal, Shloke Patel, Raj Patel(후자 두 명은 사촌 관계)에 의해 설립되었습니다. 네 명 모두 로봇 공학, 하드웨어, 촉각 데이터에 걸친 연구 배경을 가지고 있습니다. 이 회사의 설립은 AI 산업의 향방에 대한 직접적인 베팅입니다. 로봇 공학 연구소와 최첨단 AI 기업들이 현실 세계에서 물리적 작업을 수행할 수 있는 기계를 만들기 위해 경쟁함에 따라, 그들은 인간의 일상적인 업무 수행 모습을 담은 고품질의 실제 환경 훈련 데이터 부족이라는 심각한 병목 현상에 직면해 있습니다. Human Archive의 베팅은 인도의 급성장하는 긱 경제에서 일하는 노동자들이 바로 이러한 데이터의 미개척이면서 확장 가능한 원천이라는 것입니다.
Human Archive는 여러 파트너와 협력하고 있음에도 불구하고, 협력을 위해 Pronto 및 Urban Company를 포함한 인도 내 많은 가사 서비스 기업들로부터 거절당했다고 밝혔습니다. 주요 기업들로부터의 거절은 지난 주말 인도 매체 Entrackr이 Pronto가 로봇 훈련을 위한 작업자 데이터 수집을 위한 파트너십을 적극적으로 모색하고 있으며, Snabbit은 프로젝트가 무산되기 전 Human Archive와 초기 논의를 가졌다고 보도하면서 대중적으로 알려졌습니다. Urban Company의 CEO인 Abhiraj Singh Bhal은 X(구 트위터)를 통해 회사가 이러한 방식에는 참여하지 않을 것이라고 밝혔고, 이에 대해 Patel은 Urban Company가 곧 재고하지 않으면 고객 이탈로 인해 관련성을 잃을 위험이 있다고 맞받아쳤습니다. 공동 창립자인 Rushil Agarwal은 더욱 직설적으로, Pronto의 창립자 Anjali Sardana가 데이터 파트너십 아이디어를 제안했을 때 자신을 비웃으며 '바보'라고 불렀다고 게시했습니다. Pronto는 대화가 있었음을 인정하였으나, 프로젝트를 진행하지 않기로 결정했다고 밝혔습니다.
전국적으로 공장 작업장을 포함한 다양한 근무 환경에서 1인칭 관점의 데이터를 수집하는 다른 스타트업들도 있습니다. 차별화를 위해 Human Archive는 촉각 장갑, 전신 모션 캡처 슈트, 손목 카메라와 같은 추가 장치를 사용하고 개발하여 RGB-D(컬러 이미지와 실시간 깊이 정보가 짝을 이룬 데이터)와 동기화된 움직임 및 촉각 데이터를 포함한 데이터를 캡처하여 AI 연구소에 판매하고 있습니다. 이 스타트업은 비디오 데이터만으로는 충분하지 않으며, 다른 센서 데이터와 결합할 때 그 가치가 크게 높아진다고 믿습니다. Raj Patel은 TechCrunch와의 인터뷰에서 다른 연구원들에게 프로젝트를 보여주던 중 1인칭 관점 데이터를 접하게 되었고, 비디오를 촉각 데이터와 결합하고 싶었다고 말했습니다. 창립자들은 여러 연구소와 대화를 나누면서 자기중심적, 센서 기반 데이터 시장이 막 뜨거워지고 있다는 것을 깨달았고, 이를 중심으로 회사를 설립하기로 결정했습니다. 초기에는 데이터를 캡처하기 위해 임시방편이나 기성 장비를 사용했습니다. 이제는 서로 연동되어 다양한 종류의 데이터를 캡처하는 맞춤형 하드웨어를 개발하고 있습니다. 이미 50개 이상의 서로 다른 장치를 배포하여 다양한 데이터 포인트를 수집하고 있습니다. "데이터를 캡처하기 위해 우리는..."
In the last few years, India's online food delivery market has grown significantly, with both Zomato and Swiggy going public and an increase in the number of cloud kitchens. Meanwhile, startups working on home services, such as on-demand household staffing platforms, including Urban Company, Snabbit , and Pronto , have gained popularity. Silicon Valley-based start-up 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, hostel, 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 two Berkeley and two Stanford students — Samay Mani, Rushil Agarwal, Shloke Patel, and Raj Patel, the latter two being cousins. 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. 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 significantly more valuable. Raj Patel told TechCrunch that while showing the project to other researchers, they came across egocentric data and wanted to combine video with tactile force data. The founders began talking to different labs and realized that the market for egocentric and sensor-based data was just heating up, and decided to build a company around that. 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," he 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. 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 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. Topics AI , Human Archive , physical ai , robots , wing vc When you purchase through links in our articles, we may earn a small commissio