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This startup is betting India’s gig economy can train the world’s robots

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.

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.

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Repeat founder Ryan Williams raises $10M seed for an AI startup for private credit managers

Ellis AI announced Thursday its emergence from stealth with $10 million in seed funding from investors including First Round Capital, 645 Ventures, Harlem Capital, Khosla Ventures, Thrive Capital, Slow Capital, Kearny Jackson, and Ariel Alternatives CEO Mellody Hobson.

Ellis uses AI agents to tackle the fragmented workflow private credit managers deal with, including managing documents, spreadsheets, and correspondence. The company was founded by Ryan Williams, best known for co-creating the real estate investment platform Cadre alongside Josh and Jared Kushner back in 2014. That company raised more than $160 million in funding and, at its peak, was valued at $800 million before being sold for an undisclosed sum to the alternative investment company Yieldstreet in 2024.

“At Cadre, I saw the next major constraint,” Williams said. “Even as the front end of private markets became more modern and accessible, the operating infrastructure underneath it remained fragmented.”

He started working on Ellis last year. The company seeks to connect and centralize all the scattered software, accounting information, and documents a private credit firm would use into one easily accessible platform. The system can flag discrepancies in the data and uses AI agents to help perform tasks like portfolio monitoring and preparing reports.

For example, Williams promises the agents can help close a fund’s books at the end of the month.

“A team may have to download files from several systems, reformat the data, compare balances, investigate discrepancies, and re-enter information by hand. In many firms, Excel becomes the operating system,” he continued. “Ellis connects to the systems and documents a firm already uses rather than forcing it to rip everything out and start over.”

It keeps a human in the loop, too, he says. “Material decisions and actions remain with the human experts,” he said.

“I expect the human loop to become narrower, but not disappear,” he continued, when asked if he sees a day when the AI works fully autonomously. “Our goal is not to replace human judgment; it’s to help people cut through the noise and make educated decisions faster.” 

This piece was updated to add an investor.

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Tesla reportedly might sell its China business ahead of a SpaceX merger

Tesla is reportedly considering cleaving off its entire business in China to grease the wheels of a merger with SpaceX, according to the Wall Street Journal.

The newspaper reports that “some Tesla executives have been told to prepare for a separation of the China business,” which could include a “spinoff, sale or closure,” citing unnamed sources. The company reportedly would be able to do this fairly quickly because CEO Elon Musk had already tasked executives to prepare for a split in the event that Beijing invades Taiwan.

Separating China from Tesla’s global operations could make it easier to integrate the company into SpaceX, which is a defense contractor that has to follow strict rules around citizenship and national security. That would also be a major concession. China has grown to dominate Tesla’s business, not only as a market for its vehicles, but as a production hub that serves Asia more broadly, and also Europe.

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WhatsApp is testing a new folder for messages from large businesses

During Meta’s Q2 2026 earnings call, Mark Zuckerberg said that other revenue in the family of apps segment crossed $1 billion, largely thanks to WhatsApp paid messaging and subscriptions.

As more businesses use WhatsApp to reach consumers, users’ inboxes often get cluttered, making it hard to find personal and group messages. Meta is now trying out a new feature where it will place messages from larger businesses like banks or airlines in a separate folder, TechCrunch has learned exclusively.

When a user receives a message from a large business, WhatsApp will automatically move that message to a new “Offers & Updates” folder after a set number of hours. The company said it is testing different durations, up to 24 hours, to move messages to a new folder.

Users who prefer their messages to be on the timeline can turn this setting off. However, they don’t control when messages are moved automatically.

Meta said that with this feature, messages like discount codes and delivery updates are out of the inbox in a few hours, and the main chat timeline feels less cluttered. For businesses, this means that users can look for their messages in a specific folder rather than getting lost in all chats.

WhatsApp is starting to test this feature with select partners using its WhatsApp Business Platform, and will look to expand based on observations. At the moment, small businesses and individual accounts using WhatsApp Business are exempt from this feature. WhatsApp said it could explore moving business messages from small businesses to the new “Offers & Updates” folder in the future.

In the last few years, WhatsApp has taken steps to reduce business message spam. In 2024, it started allowing users to unsubscribe from marketing messages from brands. Last year, it put a curb on the number of broadcast messages businesses and individuals can send in a time frame. In October 2025, it went one step further and limited the number of messages businesses could send without getting a response from users. The company has fully rolled out the first two features while it is still iterating on the third feature.

Despite these steps, the WhatsApp inbox can feel chaotic. From my own experience, there have been days when I have cleared unread messages at the start of the day only to end with more than 30-40 unread messages. Even at the time of writing, more than half of my unread messages were business communications. I am not alone in feeling this.

The new feature might reduce the clutter a little, but it won’t be effective until users have control over filtering out messages from the main inbox.

WhatsApp made its AI business agents available globally in June, with more than 1 million businesses already using them. During the earnings call, Zuckerberg mentioned Brazil’s car rental company Movida and said that it has seen an uptick in conversions and customer support issue handling through AI agents. In the coming months, we could see more businesses use AI within WhatsApp for sales, marketing, and support use cases. A chat app with over 3 billion users must strike a balance between personal and business messages before it becomes a vehicle for AI spam.

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