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EnglishHow can traditional agriculture and animal husbandry overcome challenges such as disease risks, loose management, and data silos?
Xin Lian Poultry and Iron Rider have found a breakthrough using DingTalk's low-code platform and AI: efficient approvals, data insights, and a 24-hour AI livestock expert... DingTalk's digital intelligence capabilities are reshaping modern agriculture and animal husbandry.
Xin Lian Poultry:
Paperless chicken farming on DingTalk
Founded in 1982, Anhui Xin Lian Poultry started as an egg-laying hen breeding company and has gradually built a complete industrial chain from breeding, farming, and planting to the dining table. The company's "Hao Nian Tou" brand has become the No. 1 seller in the egg category on Douyin and Xiaohongshu, while also ranking among the top sellers on Taobao platforms, with a cumulative total of 2 billion eggs sold.
The biggest pain point for traditional animal husbandry is uncertainty. This uncertainty includes risks from diseases like avian influenza, uncertainties in the farming process, and fluctuations in raw material and market prices. In addition, the industry faces numerous challenges related to production technology, breed bottlenecks, and organizational management. Xin Lian Poultry itself has come close to bankruptcy five times.
Twenty-two years ago, Chairman Chen Hui gave up a high-paying programming job to join the chicken farm, bringing a programmer's mindset to traditional agriculture. He introduced DingTalk's low-code platform and AI to build various business applications. Take financial approvals as an example: Xin Lian Poultry's original in-house system couldn't efficiently deliver approval notifications to employees, requiring staff to check the system proactively. Moreover, data couldn't flow across different applications, and the system couldn't be flexibly adjusted to meet rapidly changing business needs. Three finance staff members used to spend two hours every day reconciling data. Chen Hui personally took charge and built the company's financial approval process on DingTalk's low-code platform in just half a day. Now, the finance department can complete data reconciliation in just one and a half hours with a single person.
Through DingTalk, Chen Hui has transformed existing legacy applications and systems into AI-powered tools with a single click, connecting scattered data points to support business decision-making. The AI assistant built by Xin Lian Poultry on DingTalk—the "Ancestor Black Chicken Management Application Assistant"—can analyze data from multiple dimensions, including sales revenue and the proportion of each product. It can also report and push results in natural language and provide recommendations, effectively acting as a data analyst that can report to you at any time.
With the help of DingTalk's low-code platform and AI, Xin Lian Poultry has achieved end-to-end digitalization—from livestock production and egg processing to profit accounting and e-commerce operations.
Iron Rider:
DingTalk AI knows pig farming better than farm managers
Founded in 1992, Iron Rider has established more than 150 branches nationwide and is a modern agricultural and livestock food group integrating feed, breeding, food, and bioengineering.
Iron Rider works with hundreds of partner farmers across the country. Farmers purchase feed and farming technology from Iron Rider, and the company then buys back the finished pigs. During the farming period, farmers scattered across different regions often consult Iron Rider's technical staff about problems encountered in pig farming—for example, what to do if pigs have diarrhea or exhibit abnormal behavior patterns. Sometimes, sows give birth in the middle of the night, and farmers seek remote guidance and assistance from the company's technical staff. Internally, due to the large number of branches and employees, along with employee turnover and other factors, training employees to use the company's 25 previously built business systems was a heavy burden.
In March last year, the company's pig farm welcomed a new member—the "Smart Livestock Expert," an AI assistant developed on DingTalk. During the training of this AI assistant, the company's digital engineers fed it three types of data: first, company rules and regulations; second, industry data and knowledge; and third, internal experience and data. Although each farm manager is an expert in pig farming, they still fall short of the AI assistant in terms of breadth of pig-farming knowledge.
The farm manager of Iron Rider's NanChuan pig farm in Chongqing speaks highly of this "new colleague": "Now, whenever we have a question, we can simply ask the AI assistant via voice. For example, if a pig shows abnormal signs and a regular farmer lacks the experience to determine whether the pig is sick, we can describe the situation to the AI assistant. The AI assistant immediately provides accurate data and knowledge, greatly reducing our workload."
In just two weeks after the AI assistant went live, more than 100 farm managers consulted it over 5,000 times. For farmers, this means receiving timely and accurate responses 24/7; for technical staff, it frees up both manpower and time.
As the agriculture and animal husbandry industries begin using AI assistants to solve complex problems, an industry transformation driven by DingTalk AI is quietly unfolding in the fields and farms.
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