The move comes after Bengaluru-based quick home services startup Pronto confirmed it was testing opt-in recordings during household tasks, triggering concerns around surveillance, consent and the use of customer-home data for AI training.

The Ministry of Electronics and Information Technology has taken cognisance of the controversy around Pronto's in-home recording pilot and is looking into the matter, government sources told Moneycontrol, bringing greater regulatory scrutiny to how startups use customer-home data for AI systems.
The development comes after Bengaluru-based home-services startup Pronto confirmed it was testing an opt-in feature involving recordings during cleaning and other household tasks, triggering debate around surveillance, consent and the use of customer-home data for AI training purposes.
The controversy also pushed rival home-services startups to publicly distance themselves from similar practices. Urban Company cofounder Abhiraj Singh Bhal and Snabbit founder Aayush Agarwal denied claims on social media that their companies were actively deploying recording systems inside customer homes.
The issue has drawn attention because of the rapid rise of India’s instant home-services segment, where startups such as Pronto, Snabbit and Urban Company are aggressively expanding rapid cleaning and household assistance offerings. Moneycontrol had earlier reported that combined monthly active users across the three platforms crossed 10 million earlier this year.
Privacy experts say the larger concern is not just the recordings themselves, but the absence of clear regulatory guardrails around how such data could eventually be reused for AI systems.
“Pronto’s collection of personal data has brought to the forefront several uncertainties within the DPDPA, 2023, particularly when it comes to the use of personal information for AI training purposes,” said Kamesh Shekar, Associate Director at The Dialogue, a technology policy think tank.
“Although Pronto may delete the underlying data after 48 hours, concerns remain around prompt-data reuse and the broader challenge that AI-generated inferences cannot simply be ‘unlearned’ like human memory,” he added.
Source: Money Control