For Meitu, the next AI product may come from data, passion, or both
Meitu, a Chinese AI-powered imaging and design company, is experiencing a resurgence, with its overseas monthly active users returning to 100 million in 2025 and revenue reaching RMB 3.858 billion (USD 569.2 million). The company's success is largely attributed to its rapid global expansion and a strategic shift towards AI-powered products, which now account for 76.6% of its revenue. Founder Wu Xinhong emphasizes speed and organic growth, implementing a strict one-month product development cycle and a USD 100,000 ARR validation standard within six months. Meitu's product strategy balances data-driven insights with the founder's personal passions, leading to both commercially successful and niche AI applications.
Meitu's turnaround highlights a critical trend in Asia's tech ecosystem: the transformative power of AI in revitalizing established companies and driving global expansion. The company's aggressive pursuit of overseas markets, particularly in Southeast Asia and Latin America, demonstrates the growing importance of internationalization for Chinese tech firms seeking new growth vectors beyond a saturated domestic market. Meitu's success in these regions, where its products frequently top download charts, underscores the universal demand for accessible and high-quality AI imaging tools. This also signals a broader shift where Chinese tech companies are not just adapting to global trends but actively shaping them, particularly in consumer-facing AI applications.
The company's dual product development approach—balancing data-driven innovation with passion-driven projects—offers a compelling model for fostering creativity and market responsiveness. This strategy, combined with a lean and agile incubation process, allows Meitu to rapidly iterate and validate products, a crucial advantage in the fast-evolving AI landscape. Furthermore, Meitu's decision to train its own large model, MiracleVision, for portrait optimization, despite being an application-layer company, reflects a strategic imperative for specialized AI development to maintain product quality and differentiation in competitive niches. This vertical integration in AI capabilities is likely to become a more common strategy for companies aiming to control core aspects of their AI-powered offerings.
