The call announced Pony AI's Q1 2026 earnings, featuring financial and operating results. Forward-looking statements were included, alongside a Q&A session. Non-GAAP measures were discussed, reconciled in the earnings release. Accessible via the investor relations website, it covered key insights from leadership.

In Q1 2026, the company achieved a 145% year-over-year revenue growth, with global taxi revenues increasing nearly 400%. The robot taxi fleet expanded to over 1,000 vehicles, supported by a more than 200% increase in registered users in China and over 100% growth in weekly paid orders. Services were broadened into downtown Guangzhou and Europe, marking the first commercial robot taxi service in Croatia's capital.

The company achieved remarkable growth in Q1, expanding its fleet and operational footprint in key Chinese cities while initiating services in international markets including Croatia, Qatar, Singapore, and South Korea. This success is attributed to the strategic focus on both domestic and global markets, technological leadership, and operational excellence, which have attracted significant partnerships and contributed to diversified revenue streams.

Company accelerates Gen 7 vehicle rollout, optimizing costs and enhancing safety through advanced L4 technology. Premium service demand surges, with weekly paid orders increasing over 100% in May. Continuous operation improvements boost fleet efficiency and reduce costs.

Pony achieved significant revenue growth across all business lines in Q1, driven by scaling long-haul operations and expanding into urban logistics. The company launched its L4 Autonomous light truck and saw a surge in autonomous domain controller shipments, particularly for low-speed delivery applications. With a commitment to safety and rigorous engineering, Pony is raising its annual targets, aiming for a fleet of over 3,500 vehicles and revenue growth beyond 3.5x. The company is confident in expanding its footprint to over 100 cities globally and domestically, leading the development of sustainable autonomous driving technology.

Solid Technology Foundation has surpassed 1700 vehicles in its testing fleet, with Q1 robot tax revenues surging by nearly 400% year-over-year. The company is raising its full-year target to over 3500 vehicles, projecting a 3.5-fold revenue increase from last year. This growth is attributed to rapid deployment in high-value markets, such as the downtown core of Guangzhou and Europe's first commercial tax service, showcasing technological leadership. The company's successful management of extreme localized demand during a concert in Guangzhou, integrating with official traffic plans, highlights its safety and operational capability, bolstered by core technical pillars: exceptional training, operational redundancy, and efficient speed management. This performance underscores the public's higher standards for L4 autonomous driving compared to human drivers.

Discusses the shift from human-like AI to advanced autonomous driving, emphasizing the importance of reinforced learning and multi-layer redundancy for achieving L4 safety standards, surpassing human capabilities in complex environments.

The system ensures vehicle safety and functionality even during component failures, network outages, or GPS signal loss. It adapts to real-time conditions, detects collisions instantly, and prevents damage from water wading. Citywide safety is maintained through scalable intelligence, ensuring fleet-wide protection.

Discusses a three-tier safety strategy including prevention, detection, and response for autonomous vehicles, highlighting the company's focus on safety and scalability with plans to expand its fleet to over 3,500 vehicles in more than 20 cities by year-end, aiming to unlock greater commercial value while maintaining a trusted service.

The company achieved a 145% increase in total revenue to $34.3 million, with robotic taxi and truck services leading growth. Robotic taxi revenue soared 456%, and robotic truck services grew 31%, reflecting strong market demand and operational efficiency.

The intelligent solution segment saw a 206% revenue growth to $15.5M, driven by Atom's domain controllers. Despite a net loss of $53.5M, loss margins narrowed significantly. The company maintained a robust financial position with $1.4B in cash and investments, and increased capital expenditures for Gen 7 vehicle production and data center investments.

The dialogue highlights the company's robust safety measures and regulatory cooperation, assuring stakeholders that current policy shifts won't hinder its ambitious growth targets. Emphasizing its leadership in dense urban autonomous driving, the company foresees market consolidation, benefiting its long-term industry dominance.

The company revised its revenue and fleet size targets upwards, attributing the change to strong commercial momentum, particularly in domestic operations, and successful joint deployments in Shenzhen and Guangzhou. This has attracted potential partners and increased confidence in achieving higher global taxi revenue growth and expanding the fleet to 3,500 vehicles by year-end.

Baidu's launch of L4 autonomous light truck aligns with its vision for autonomous mobility, aiming to complete its logistics portfolio by integrating technology across various vehicle platforms. The initiative leverages existing infrastructure, promising cost efficiencies and operational synergies, with plans for scalable operations by early next year.

A query on Pony.ai's strategy regarding VLA models in autonomous driving explores the necessity of the language component amidst trends of its removal by competitors, seeking insights into future technological advancements.

The dialogue emphasizes the importance of an intention layer in driving models for predicting and responding to the intentions of other road users, ensuring safety in all scenarios, including low probability edge cases. It argues against the use of language models in automotive applications due to their high computational demands and lack of suitability for real-time driving safety. Instead, it advocates for the use of world models and generated intention data for robust training, highlighting the necessity of a virtual driving environment for safe model development and deployment.

The dialogue discusses the importance of balancing high growth with strategic investments, emphasizing disciplined value-driven expenditures to maintain a strong growth trajectory and competitive edge in the industry.

The dialogue highlights the company's strategic efforts in global expansion, emphasizing its dual engine approach and prioritization of key regions including the Middle East, Europe, and Asia. It showcases current market presence, partnerships, and plans to scale operations to over 20 cities worldwide, leveraging proven technology and regulatory support.

Discussion focused on strategies to reduce bond costs through volume discounts, system optimization based on real data, and proactive supply chain management, aiming to meet the target of reducing costs to 230K by mid-next year despite uncertainties.

Call is ended, thanking participants and inviting further contact with the relations team for any future queries, concluding the session with anticipation of future communication.