PT Transportasi Jakarta (Transjakarta) continues to drive digital transformation by developing three artificial intelligence (AI)-based technologies to make its service and operational systems smarter, more efficient, and more responsive to customer needs.

Transjakarta Director of Information Technology System and Service, Raditya Maulana Rusdi, said this initiative is part of the company's broader digitalization map that positioning technology as the main driver of public transportation service evolution.

"The development of AI-based service systems ensures each customer receives faster, more personalized, and safer experiences. This technology will serve as a key foundation for building a more integrated and sustainable public transportation system in the future," he stated on Thursday (7/17).

Besides technology, he added, this transformation also targets a shift in mindset and internal capabilities. He emphasized that adopting AI is not only about systems, but also about human readiness.

"We are fostering a new work culture where all personnel understand the role of data and AI in creating significantly improved public services," he mentioned.

Here are three AI technologies that currently being developed by Transjakarta:

1. AIText: Advancing Services with AI Agent and Agentic AI

Transjakarta is developing a generative AI-based agent capable of interacting naturally with customers via chatbot and text-to-speech features. This AI agent goes beyond simply answering question, but it is designed as an Agentic AI that can understand context, make decisions, and actively provide information, such as route details, bus arrival times, or lost-and-found assistance.

2. AIVision: Machine Vision for AI Technology Operations

This system use computer vision from CCTV data streams to detect passenger volume at bus stops, monitor fleet movement, and support data-driven operational efficiency. As part of its safety system, Transjakarta has also begun implementing a Driver Monitoring System (DMS) that tracks driver behaviour in real time to ensure high safety standards.

3. Recommendation Engine: Analytics for Smarter Decision-Making

This system is designed to analyze service-related big data and customer travel patterns to provide strategic recommendations, from new route recommendations, increased fleet frequency, to potential data-driven partnership opportunities.