After Reducing Costs by 90% with AI Customer Service, DingTalk Aims to Help Enterprises Implement Dedicated Large Models

At the 10th anniversary and AI Lingdang 1.0 product launch event, Lingdang announced that it will leverage its technological capabilities—from data resource preparation to industry-specific model training and application deployment—to help enterprises build their own dedicated AI systems.

Lingdang CEO Wuzhao: Building Dedicated AI Is a Systematic Project

During the launch event, Lingdang CEO Wuzhao revealed that Lingdang has already implemented industry- or enterprise-specific large models and AI applications in sectors such as healthcare and industrial manufacturing. The company has also developed its own AI customer service model, significantly improving service efficiency and customer satisfaction while reducing costs by 90%.

Wuzhao stated: "Building dedicated AI is a systematic project. Enterprises can implement dedicated AI across four layers: data resources, understanding and reasoning, decision-making and action, and reflection and evolution. Lingdang offers full-chain support from data preparation to model training and autonomous decision-making, empowering companies to deploy custom large models and AI applications from scratch."

Data Preparation: Turning Enterprise Knowledge into a "Flowing Source"

At the data level, Lingdang uses an AI search engine, AI knowledge base, and continuous data updating system to help businesses aggregate and organize knowledge suitable for AI learning, transforming data into rich nourishment for training industry-specific large models.

Reasoning and Refinement: Creating an "Industry-Savvy Expert Model"

Leveraging hands-on experience with its own customer service large model, Lingdang helps enterprises convert raw data into high-quality, low-noise "real question banks" to enhance model training effectiveness. At the same time, Lingdang offers customized industry large model services—enterprises need only provide domain experts to collaborate in co-developing truly industry-savvy models.

Decision-Making and Action: Deep Integration of AI into Business Processes

At the decision-making level, Lingdang enables AI to deeply integrate into business workflows, allowing autonomous analysis, system calls, and execution of actions to directly solve real-world problems. For example, in the metallurgy industry, Lingdang helped a client build an operations optimization model that automatically generates raw material mixing plans, increasing product yield by nearly 10%.

Industry-Education Collaboration: Partnering with Zhejiang University to Build an AI Innovation Platform

To accelerate AI adoption across more industries, Lingdang signed a strategic cooperation agreement with the Zhejiang Provincial Key Laboratory of Digital Management and Decision Technology (Zhejiang University) to jointly establish an "AI Industry-Education Integrated Innovation Platform." By combining technical platforms with industry know-how, they will work with academic professors to advance industry-specific large models and AI solution development.

Lingdang CTO Yisu: Self-Trained Models Are the Key Path Forward

Lingdang CTO Yisu said: "Enterprise-specific large models are poised for explosive growth, and self-trained models will become the key path for enterprises adopting AI." Currently, Lingdang has formed a dedicated team for industry large models and is actively advancing AI implementation—not only achieving efficiency gains and cost reductions internally but also delivering significant performance improvements for clients in healthcare, manufacturing, finance, and other fields.

AI Customer Service Practice: Satisfaction Up to 80%, Costs Down by 90%

By training its proprietary AI customer service large model, Lingdang increased genuine customer satisfaction from 30% to 80% and reduced customer service costs by 90%. Traditional service systems struggle to respond to high volumes of demand, whereas Lingdang has built a professional team to train AI agents capable of providing 24/7 instant responses.

Currently, Lingdang's AI customer service has seen a significant improvement in response accuracy and can now coordinate with product development teams to follow up on customer needs, ensuring "every request receives a response, every issue finds resolution." The customer service team itself has transitioned into an AI data engineering team, enabling broader AI customer service implementations across industries.

Healthcare Case: Doukou Gynecology Model Achieves 90.2% Accuracy

In healthcare, Lingdang partnered with Yisheng Jiankang to successfully train the Doukou Gynecology Large Model (doukou.ai), a model with capabilities approaching those of professional doctors, setting a benchmark for industry-specific large model development among small and medium-sized enterprises.

Lingdang provided end-to-end support—from data governance and efficient training to flexible deployment—reducing single training time from 26 hours to just 7 hours and improving diagnostic accuracy from 77% to 90.2%.

Chen Yu, product lead for Doukou, said: "Lingdang not only provides training resources but also shares methodologies, greatly improving our training efficiency and accelerating model iteration and upgrades."

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