Singapore’s Grab taps Solana DePIN project Natix to ‘reshape mapping’
Southeast Asia’s superapp Grab has partnered with Natix, a project within Solana’s decentralized physical infrastructure network (DePIN), to cooperate on mapping and autonomous driving technologies.The joint collaboratio...
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Southeast Asia’s superapp Grab has partnered with Natix, a project within Solana’s decentralized physical infrastructure network (DePIN), to cooperate on mapping and autonomous driving technologies.
The joint collaboration aims to combine Natix’s blockchain-based mapping data with Grab’s camera hardware and mapmaking technology featuring artificial intelligence support, Natix said in an announcement on May 6.
“This partnership brings together the best of both worlds,” the announcement noted, pointing to Grab’s expertise in crowdsourced mapping and Natix’s unique DePIN model that rewards users for providing decentralized data input.
Source: Natix“By combining GrabMaps’ AI-powered mapping technology with Natix’s decentralized data network, we’re enabling real-time, high-fidelity map updates across the globe,” Grab’s mapping service, GrabMaps, wrote in a LinkedIn post on Tuesday.
360° vehicle imagery for Tesla driversAs part of the collaboration, Natix will launch VX360, a device built on Grab’s hardware platform that allows Tesla drivers to collect and share 360° vehicle imagery, GrabMaps said in the LinkedIn statement.
“This rich visual data powers fresher maps and provides critical training and validation datasets for autonomous driving and physical AI applications,” it added.
GrabMaps announced a partnership with the Natix Network on LinkedIn. Source: GrabMapsApart from Natix, GrabMaps has also collaborated on hyperlocal location map-making tech with partners like Loqate, Bing Maps, Mappls and more, according to its official website.
Driving data incentives for better mappingAccording to Natix, traditional centralized mapping methods like Google Street View and TomTom are inefficient, expensive and are often associated with limited coverage and update frequency, requiring firms to invest considerable sums to update maps.
To solve this problem, Natix has built an on-street camera network, which enables crowdsourced models to gather real-time data from users’ devices about road conditions and changes at a “fraction of the cost,” Natix co-founder and CEO Alireza Ghods told Cointelegraph.
“Google has started tapping into this model by asking users to submit road updates, but the data remains proprietary. It is expensive to access and only available in the territories that companies pay for,” he noted, adding:
“A blockchain-based incentivization system provides better results in terms of frequency, participation, and coverage.”“We’re giving Tesla drivers access and storage for their vehicle’s camera feed — while earning rewards for contributing 360° imagery that will be used for better mapping solutions and to power physical AI,” Natix said in the announcement.
Source: NatixFor the tech to pay attention to map events like accidents and roadwork as well as traffic signs, Natix has also been building AI pipelines for the extraction of data, Ghods said, adding:
“Some are internal efforts, and now we plan to tap into Grab’s AI capabilities as they have cutting-edge technology already built for this need.”
Grab’s growing interest in crypto and blockchainGrab’s new partnership with Natix is another milestone in the company’s growing number of blockchain and cryptocurrency adoption use cases.
In March 2024, Grab partnered with the payments firm Triple-A to enable its clients to pay for services using five cryptocurrencies, including Bitcoin (BTC), Ether (ETH) and Circle’s USDC (USDC) stablecoin.
An excerpt from Circle’s case study on Grab. Source: CircleAdditionally, Grab is significantly backed by the Japanese multinational investment holding company SoftBank, which is known for its bullish stance on cryptocurrency and AI.
The news comes shortly after Grab reported $773 million of revenue in the first quarter of 2025, posting an 18% increase year-over-year.
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