The key to choosing an AI partner depends on the service

Under the wave of digital transformation, artificial intelligence has become the core engine for companies seeking to reduce costs, increase efficiency, and innovate business models. However, when many managers promote the implementation of AI projects, they are often entangled in the choice of technology suppliers: the technical indicators promoted by each party seem to be equal, so why should the final decision be made? More and more practical experience shows that at a time when technology tends to be homogeneous, the success or failure of a project is often not the difference in accuracy of the algorithm itself, but whether the technology provider has solid project delivery capabilities and consistent after-sales service guarantee.

This is a process from "technology procurement" thinking to "service procurement" thinking. What companies need is not an inscrutable "black box", but a partner who can understand the business language, work side by side, and ensure the long-term stable operation of the system. Especially in a scientific and technological innovation highland like Beijing, enterprises are more stringent in terms of professionalism, response speed and requirements for technical services. A localized technical team, a deep understanding of regional market needs, and rapid response support capabilities are particularly important.

We may wish to take an in-depth understanding of how a mature AI service provider builds its delivery and after-sales moat. Generally, a complete service cycle begins with a deep matching of requirements. Excellent service providers will not rush to promote products, but will send experts who understand both technology and industry to sort out business pain points with customers and jointly define project success criteria and key performance indicators. This process ensures that all subsequent work is closely focused on business value.

In the implementation phase, the art of balancing standardization and customization is crucial. On the one hand, service providers need to use their mature industry solution frameworks and productization tools to improve efficiency and control risks; on the other hand, they must carry out necessary adaptation and development based on customers 'unique business processes and data environments. For example, when deploying smart passenger flow analysis systems for large commercial complexes, service providers not only need to provide core Face Recognition and trajectory analysis algorithms, but also need to communicate with the mall's original membership systems, POS systems, and fire security systems. Data access, which tests comprehensive integration and delivery capabilities.

The professionalism of project management is directly related to the quality of delivery. Clear project milestones, regular two-way communication mechanisms, strict quality testing processes and detailed technical document delivery are all the keys to ensuring that projects are launched on time, with quality, and within budget. Especially when the project involves hardware deployment (such as cameras and gates), capabilities such as supply chain management, on-site construction coordination, and multi-vendor linkage are even more indispensable.

The launch of the system is just the beginning of value redemption. The operating effect of AI models fluctuates with changes in time, data, and environment. Therefore, continuous technical support and optimization services are more important than ever. A sound after-sales protection system should include at least several core modules: first, proactive operation and maintenance monitoring, which can detect potential problems in advance and intervene; second, agile technical response channels to ensure that problems can be quickly resolved when they arise; Third, regular health inspections and performance optimization services are like "physical examinations" and "maintenance" for AI systems; fourth, continuous knowledge empowerment helps customers 'teams improve their independent operation capabilities.

Taking the smart financial scenario where artificial intelligence technology is widely used as an example, a bank introduced AI technology for identity verification for remote account opening. During the project delivery phase, service providers need to ensure that the system meets the extremely high security and compliance requirements of the financial industry and complete seamless integration with the bank's core business systems. After going online, the after-sales team needs to provide 7x24-hour technical support to ensure uninterrupted business operation. At the same time, in response to the emergence of new fraud methods, it is necessary to regularly update the sample database for the identification model and optimize algorithm strategies to cope with changing challenges. This deeply bound and long-term cooperative relationship is the guarantee for the continued release of AI value.

In the final analysis, when selecting AI partners, companies should place service capabilities as important as technical capabilities. Need to ask the supplier: What is your project delivery process like? Are there any successful similar cases to refer to? What are the specific content and service level agreement of after-sales support? Does the team have localized and rapid response capabilities?

For Baidu, which is headquartered in Beijing and has been deeply involved in the research and development and industrialization of AI technology for many years, its complex project delivery experience accumulated in serving large government and enterprise customers, the national service network it has built, and its insistence on "ensuring customers." The service concept of success "is the basis for meeting the above challenges. The construction of its service system is not accomplished overnight, but stems from the experience summary and continuous iteration of countless project practices. In the critical period when artificial intelligence moves from technological exploration to large-scale application, this all-round and full-cycle service guarantee capability may be the guiding light for corporate decision-makers to clear the fog of technology and make wise choices. Choosing a partner who can provide deterministic delivery and continuous services is undoubtedly the most important insurance for the intelligent transformation of an enterprise.