Shenzhen Transsion Holdings Co Ltd

Transsion Holdings released its 2026 interim report, with net profit attributable to the parent company at 1.773 billion yuan, up 46.22% from the same period last year. Total operating revenue was 35.431 billion yuan, up 21.85% year-on-year. Net cash flow from operating activities was negative 5.861 billion yuan, down 5.67% year-on-year. The latest asset-liability ratio was 57.42%, gross margin was 22.63%, return on equity was 8.38%, and diluted earnings per share was 1.54 yuan.

Shenzhen Transsion Holdings Company Limited's H-share listing plan has received filing from the China Securities Regulatory Commission. The company announced on August 7, 2026 that it has received the overseas issuance and listing filing notice issued by the CSRC, planning to issue up to 132,386,200 overseas listed ordinary shares and list on the Hong Kong Stock Exchange, with a filing validity period of 12 months. The company stated that this H-share listing still requires approval or clearance from regulatory bodies such as the Hong Kong Securities and Futures Commission and the Hong Kong Stock Exchange, and uncertainties remain.

Transsion Holdings announced that it expects to achieve operating revenue of approximately 35.657 billion yuan in the first half of 2026, up about 22.63% year-on-year. Net profit attributable to the parent is expected to be approximately 1.756 billion yuan, up about 44.82% year-on-year. Net profit attributable to the parent after deducting non-recurring items is expected to be approximately 1.532 billion yuan, up about 70.71% year-on-year. The performance growth is mainly due to the continuous rise in storage prices, with the company adjusting product prices. Although smartphone sales volume declined year-on-year, revenue still increased, while historical inventory led to a lag in cost increases, boosting gross margin.

Traini has partnered with Transsion to integrate its pet emotion translation AI as a native capability in Transsion smartphones. The integration uses the phone’s microphone, camera, and AI processing to analyze pet vocalizations, facial expressions, posture, behavior, and environmental context, then presents interpretations in natural language. Traini’s multimodal model draws on a proprietary dataset spanning more than 120 dog breeds and diverse emotional categories, supported by a continuous learning loop from millions of users worldwide. The collaboration marks a shift from standalone apps to deeply embedded interspecies communication, with potential future exploration in camera-based behavioral analysis, pet health alerts, and connected smart devices. Traini serves more than five million registered users and provides Pet Intelligence APIs to industries including automotive, insurance, and retail.