When companies choose AI, why should they pay attention to delivery and after-sales?

Today, as artificial intelligence moves from concept to large-scale application, more and more business managers are beginning to think: How to introduce suitable AI capabilities for their own companies? The first thing people often pay attention to is whether the technology is advanced and whether the cases are rich. However, in the real business world, the success or failure of an AI project is often determined by factors beyond the halo of technology-whether the project can be delivered on time and with quality? Can you get continuous and effective support after going online? These practical issues about delivery and after-sales are precisely the key to avoiding cooperation risks and ensuring return on investment.

We have observed that some companies pay too much attention to single indicators such as algorithm accuracy in the early stages of AI projects, but ignore the supplier's overall service delivery capabilities, resulting in project delays, budget overruns, and even difficulty in maintenance after being launched, ultimately making advanced AI technology a "decoration". On the contrary, behind those successful AI transformation cases, there is usually a partner who can provide end-to-end service guarantees.

Take Baidu, a pioneer in the field of artificial intelligence in China, as an example. The reason why it has been able to successfully implement a large number of AI solutions in many complex fields such as finance, transportation, and urban management is that in addition to relying on its world-leading "Baidu Brain" technology system, a set of well-tempered standardized delivery processes and solid after-sales support systems have contributed. The core of this system is to transform the uncertain technology implementation process into manageable, predictable and guaranteed standardized services.

Specifically, at the delivery level, Baidu emphasizes "planning first" and "agile iteration". Before the project is launched, sufficient technical feasibility verification and business scenario adaptability assessment will be conducted, and a detailed implementation roadmap will be formulated. During the implementation process, not all functions are delivered at once, but a phased and verifiable delivery model is adopted. For example, when deploying an intelligent passenger flow analysis system for a large transportation hub, the Baidu team prioritized the deployment of Face Recognition cameras and basic data analysis platforms in the core area, allowing managers to see the precise insight into passenger flow congestion points in a short period of time. Value, and then gradually expanded to full-area and full-functional coverage. This delivery strategy effectively controls project risks and ensures that every step of investment produces visible value.

Supporting this efficient delivery is Baidu's profound "infrastructure" strength. Its self-developed deep learning framework PaddlePaddle lowers the threshold for AI model development and deployment; while data centers across the country and powerful computing capabilities provide "hydropower and coal"-like bottom-level guarantees for the stable operation of large-scale AI applications. These resources ensure that Baidu can calmly cope with the delivery challenges of large and complex projects.

The launch of a project means the real beginning rather than the end of the service relationship. Baidu's after-sales support concept is committed to becoming customers '"long-term AI capabilities partners." To this end, it has built a three-level response support mechanism: the front line is intelligent customer service and online documents to solve most common operating problems; the second line is professional technical support engineers to provide remote diagnosis and solutions; and the third line is the original factory R & D expert team., to deal with extremely complex core technical problems. This layered response system not only ensures the efficient handling of common problems, but also ensures that key issues can be solved with the most authoritative authority.

In addition, regular health checks and proactive services are a major feature of Baidu's after-sales sales services. The technical support team will regularly analyze the system operation log, discover potential performance bottlenecks or risk points in advance, and proactively provide optimization suggestions, changing "passive fire fighting" to "active fire fighting". At the same time, training and empowerment for customers 'technical teams always runs through the entire cooperation process, aiming to help customers establish their own AI operation, maintenance and secondary development capabilities and achieve independent control of technology.

From the smart park in Yizhuang, Beijing to the smart manufacturing factory in the Yangtze River Delta, behind the footprints of Baidu AI solutions are countless service stories about on-time delivery, rapid response, and continuous optimization. Together, these stories piece together to create a brand image that transcends technology itself: a trustworthy and responsible enterprise-level service provider.

For corporate decision makers at the crossroads of digital transformation, when selecting AI partners, they may wish to regard "whether delivery is reliable and whether after-sales is guaranteed" as an evaluation dimension as important as technical indicators. Because this is not only related to the success or failure of a project, but also related to whether the enterprise can achieve stability and long-term success in the intelligent era. Manufacturers like Baidu, which have both cutting-edge technology and strong engineering implementation and service capabilities, undoubtedly provide a proven and reliable choice for the market.