Grab has highlighted four ways its artificial intelligence technology is being used to solve real-world user challenges across navigation, food ordering, ride booking, and delivery services (13/01).

Artificial intelligence plays a key role in how Grab innovates and improves how consumers interact with everyday services on its platform, according to the company.

Reduce Navigation Friction with Visual Pickup Guides

Passengers often face difficulties reaching pickup points in unfamiliar locations such as large malls or busy airports.

To address this, Grab has introduced video walkthroughs that guide users to pickup points by using existing visual data. AI tools stitch static photos into immersive walkthrough videos, reducing the need for manual video production.

This allows Grab to roll out video guides more quickly across locations, helping to reduce confusion, minimise waiting times, and prevent unnecessary ride cancellations.

Overcome Language Barriers in Local Menu Translations

Language barriers can make it difficult for users to order food from local merchants.

Grab’s AI models are trained on regional food terms to provide accurate menu translations that generic translation tools often fail to deliver. This enables users to explore and order from local eateries in their preferred language.

Users can tap a translation icon in the app to instantly view menu items in their chosen language.

Improve Ride Booking Accessibility with Voice Technology

Grab has introduced an AI Voice Assistant to support visually impaired users when booking rides.

The feature uses large language models and voice recognition to allow users to speak their intent. It guides users through the ride booking process and provides updates on driver status from matching to arrival.

This allows users to book rides more easily and independently.

Enhance Delivery Reliability for Large Orders

Large food or grocery orders can be difficult for delivery-partners to handle, especially those using motorcycles.

Grab has implemented an automated system that splits large orders between two delivery partners at no extra cost to customers. A large language model evaluates orders based on size and weight to determine when a split is needed.

Delivery-partners can also request a split if they find an order too large, even if it was not flagged by the system. Customers can track each delivery separately within the app.

PHOTO: GRAB

This article was created with AI assistance.

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