Key takeaway

The company has focused on process industry automation for more than 30 years. Its DCS/SIS has ranked No.1 in China for many consecutive years. Control entry points, on-site data, and process know-how form the foundation for TPT deployment. TPT 2.0 leverages MoE and an Agent platform to drive industrial AI from predictive analysis toward closed-loop execution. UCS/APEX/AOP further strengthen capabilities in control execution, mechanism simulation, and autonomous operation. We expect the company’s operating revenue in 2026–2028 to reach RMB9.288bn/RMB10.550bn/RMB11.950bn, up 15.05%/13.60%/13.27% YoY. Net profit attributable to shareholders of the parent company is projected at RMB694mn/RMB977mn/RMB1.255bn, up 57.18%/40.74%/28.54% YoY. The corresponding PE is 125x/89x/69x. We assign a “Buy” rating.

Thesis

With more than three decades of deep expertise in process automation, TPT is empowered with execution capabilities through its access to the control layer The company has upgraded from a DCS leader to a platformbased company covering control systems, industrial software, instruments and meters, and intelligent manufacturing solutions. DCS/UCS connect field sensors, controllers, valves, and instruments, enabling TPT output to evolve from analytical recommendations into executable control strategies.

TPT 2.0 upgraded to a MoE + Agent platform: Reshaping the AI paradigm in the process industry

TPT 1.0 has validated cross-task, cross-scenario, and cross-unit capabilities. TPT 2.0 further strengthens capabilities in simulation, control, optimization, prediction, and evaluation, and enables deployment in safety, quality, low-carbon, and efficiency scenarios through an industrial Agent generation platform.

Commercialization shifts from benchmark validation to large-scale replication: Industrial AI business enters a rampup phase

In 1Q26, the company’s industrial AI revenue reached RMB184mn. A single quarter already exceeded the cumulative TPT revenue in the first three quarters of 2025. The equity incentive plan targets industrial AI revenue of RMB1.0bn/RMB2.5bn/RMB5.0bn for 2026–2028, reflecting the company’s confidence in the pace of future replication.

High-margin AI business drives margin recovery: The valuation framework may shift Traditional automation business provides the core customer base and control system foundation, while TPT/Agent subscription and model services feature high gross margin and strong scalability. As the share of industrial AI revenue increases, the company’s valuation logic is expected to shift from a traditional PE framework to a composite pricing model of traditional business + industrial AI business.

Risks:

(1) AI penetration below expectations:If TPT penetration speed, standardized replication capability, or subscription renewal rates fall short of expectations, industrial AI revenue growth may fail to match earlier R&D investment and valuation expectations. The timing for realizing the company’s second growth curve will remain uncertain.

(2) Weak recovery in the process automation industry:A weaker-than-expected recovery in the process automation industry may weigh on the performance of the company’s traditional business. The company’s traditional business is highly correlated with the macroeconomic cycle and capital expenditure in downstream process industries such as petrochemicals, chemicals, and building materials. If the domestic macroeconomic recovery remains weak and downstream capital expenditure stays sluggish, it may drag on the recovery of revenue and profit in the company’s traditional business and affect its ability to sustain investment in new businesses.

(3) Business model transition affecting short-term financial statements:The shift in business model from a one-time buyout system to a subscription system may delay revenue recognition in the short term and put pressure on financial results. Some clients may also show low acceptance of the new payment model, affecting order conversion efficiency. New businesses such as industrial AI and robotics remain small in scale, require substantial R&D investment, and have long monetization cycles. It is difficult for them to support earnings growth in the short term.

(4) Risks from overseas expansion and intensifying competition:The company has actively expanded into overseas markets for many years, and its core products and solutions now cover more than 60 countries and regions. Given the complex and evolving global political and economic environment, different countries and regions may present political, financial, sovereign, exchange rate, and compliance risks. These factors may create uncertainty for the delivery and payment collection of the company’s overseas projects. As industrial AI increasingly becomes a key driver of intelligent manufacturing, its market attractiveness continues to rise. More vendors are expected to enter this field, and superior technological paths or strong competitors may emerge, potentially weakening the company’s first-mover advantage. Meanwhile, international giants such as Siemens and Honeywell still maintain brand and technological advantages in the high-end market. To this end, the company needs to maintain its existing advantages in the industrial automation field while accelerating technological innovation, product optimization, and service upgrades in industrial AI, so as to respond to changes in the market environment in a more agile and efficient manner.