Synopsis
Recent data-gathering pilots by on-demand service platforms Pronto and Snabbit have drawn a spotlight on India’s emerging physical AI ecosystem – and put safety regulators on edge. Sources told ET that the Ministry of Electronics and Information Technology (MeitY) has taken note of recent developments, especially Pronto’s in-home recording pilots.Listen to this article in summarized format
Sources told ET that the Ministry of Electronics and Information Technology (MeitY) has taken note of recent developments, particularly around Pronto’s in-home recording pilots. Detailed queries sent to MeitY on whether the government will consider mandatory audit requirements for companies collecting sensitive real-world activity data through wearables or AI systems remained unanswered until the publication of this report.
Lightspeed-backed Snabbit conducted a pilot in April with Y Combinator-backed Human Archive. A Snabbit spokesperson told ET that the company had evaluated a preliminary proposal within a controlled training-centre environment but did not proceed further.
The developments underscore growing interest among Indian entrepreneurs and investors in physical AI, an emerging category focused on training AI systems to understand movement, physical environments and real-world tasks.
Legal experts, however, warned that AI-enabled wearable devices and recording systems expose gaps in current privacy frameworks by creating risks beyond traditional forms of data collection.
While India has a legal foundation through the Digital Personal Data Protection (DPDP) Act, 2023, the Information Technology Act and constitutional privacy principles, AI-linked recordings inside homes raise concerns around “continuous observation, behavioural profiling and inferential analysis,” according to Anushkaa Arora, principal and founder of New Delhi-based ABA Law Office.
She said “targeted regulations specifically addressing AI-assisted surveillance, retention of recordings and accountability mechanisms” would provide greater legal clarity.
Points of collection
Several startups including Human Archive, Humyn Labs, Aura ML, Build AI and FPV Labs are working on egocentric data collection and processing.
The global physical AI market is projected to grow to $15.24 billion by 2032 from $1.50 billion in 2026, according to a MarketandMarkets report.
“The wave of robotics is the next big thing in AI. Startups need to partner with organisations and companies to get access to data which is essential for training. We don’t know how much adoption will happen in India due to the safety concerns,” said an investor who has backed one of these service startups.
A person in the data collection industry said many firms are trying to sell such datasets to AI labs in the US, where physical AI is more advanced. “Earlier, companies could get rates in the range of $10-15 per hour for such datasets. But now the market has become crowded, so rates have dropped to around $3-4 per hour,” the person said.
How it works
A Bengaluru-based physical AI lab said it sources data from agri-farms, kitchens and industrial manufacturing sites depending on customer requirements. Another startup said it is working with garment factories in Gujarat to collect tailoring-related data.
“I think the appetite for this kind of data is going to be huge because almost nothing exists today, even for something as simple as folding a cloth. You need a massive amount of human-generated data for these systems to learn,” a founder at an AI lab said, requesting anonymity.
The footage being collected spans routine activities such as shopping and home organisation, as well as skilled tasks including soldering and assembly work, helping train AI systems across varied scenarios while reducing errors and hallucinations.
The videos are typically captured through wearable devices worn by workers or professionals, recording tasks from a first-person perspective.
“The Pro (professional) wears a camera that faces outward at the work itself. We also have a system in place to automatically blur any personally identifiable information before footage is ever uploaded,” Pronto said in a statement.
Data collection challenge
Unlike software AI, where internet text and images can be scraped at scale, physical AI requires real-world data that is significantly harder and more expensive to collect because models must understand movement, physics and environmental unpredictability.
Humyn Labs founder and former Nazara Technologies CEO Manish Agarwal, had told ET in April, “We are collecting the raw data, processing it for subjective validations, sending it for labelling and annotation, and then putting it through system quality checks.”
Humyn Labs announced a $20 million investment in physical AI infrastructure in April. While the US remains its primary customer market, the Global South acts as the supply side, Agarwal had said.
Manav Robotics, founded by former Ola executives Suvonil Chatterjee and Slokarth Dash, is also building humanoid robotics systems deployed in factories. “
“Our robots work inside live factories, so they will naturally see workers, ID cards, machine names, logos. We anonymise everything end-to-end and obfuscate all personal identity information before any data leaves the site. That’s contractually built into every partnership,” Chatterjee said.
He added that the firm directly works with its partner companies on both deployment and joint technology development, owning the full data pipeline in-house.
