AI Project Avoidance Guide: Delivery and after-sales are the key

Under the wave of digital transformation, AI projects have become a new track for companies to compete for investment. But behind the high expectations, there are many "pits" hidden: the project is unfinished, the effect is not as expected, and it becomes a maintenance "black hole" after being launched... These problems have discouraged many B-end buyers. In fact, the key to avoiding these pits is to strictly examine the supplier's "delivery capabilities" and "after-sales guarantees" before the project is launched. This is not only the terms of service, but also the "safety rope" for the success of the project.

Why are delivery and after-sales so important? Because AI projects are highly complex and uncertain. It is different from purchasing standardized software and often involves multiple aspects such as algorithm customization, data cleaning, system integration and business process transformation. If one link fails, it may lead to overall failure. Therefore, whether suppliers have mature methodologies and rich practical experience to manage this complexity is crucial.

First of all, looking at delivery depends on whether it has the ability to "turnkey" projects. This is not just about deploying code to a server, but covers a complete closed loop from planning, design, development, testing to training and launch.

During the planning stage, reliable service providers should send consultants who understand both technology and business to go deep into the front line to understand the real pain points, rather than simply applying templates. During the design stage, detailed technical architecture and interface plans should be output to clarify the responsibilities of all parties. In the development and testing phase, an agile iterative approach should be adopted to allow customers to see the prototype early and give feedback to avoid discovering that "this is not what I want" during final acceptance.

We have observed that some leading companies that have been deeply involved in the field of artificial intelligence for many years have formed a replicable industry solution delivery suite. For example, in smart cultural tourism scenarios, they can quickly combine modules such as face ticket checking, crowd analysis, and intelligent navigation, greatly shortening the customized development cycle and improving delivery efficiency and quality predictability. This "experience base" accumulated based on a large number of projects is unmatched by novice companies.

Secondly, the level of communication and project management during the delivery process directly determines the experience. Regular project progress synchronization meetings, clear problem tracking lists, and professional change management processes can all reflect the professionalism of a team. The purchaser should pay attention to the role of the project manager, who should be the spokesperson of the customer and be responsible for coordinating internal resources to ensure that the project progresses in accordance with the set goals.

The project was successfully launched and after cheering, the real long-term cooperation has just begun. The after-sales guarantee system is the touchstone for testing the sincerity of suppliers. A complete set of after-sales guarantees should be like a car's "4S shop" service, including:

1. Warranty and emergency rescue: The ability to respond quickly and repair when a system fails. Clear service-level agreements are key, for example, promising to respond to core system failures within 2 hours and recover within 4 hours.
2. Regular maintenance and testing: AI models require "maintenance". Suppliers should regularly provide model performance evaluation reports to monitor whether it is "degraded" due to data changes, and provide optimization suggestions or re-training services.
3. Software upgrades and functional enhancements: Technology is changing with each passing day. Suppliers should plan the technological evolution path for the solutions they provide and provide necessary security patches and functional enhancement packages during the contract period.
4. Knowledge base and community support: In addition to manual services, rich online documents, frequently asked questions answers and developer communities allow customers 'technical teams to solve most problems independently and improve efficiency.

Especially for companies from highlands of technological innovation such as Beijing, their after-sales teams can often be directly linked to cutting-edge R & D resources. When customers encounter difficult technical problems, this "R & D" back-office support capability can often find the root cause and propose solutions faster.

When evaluating potential partners, companies can ask some specific questions to examine their service capabilities: "Can you provide a complete delivery cycle for similar projects?" "What is the structure of the after-sales support team? Is there any support from original R & D engineers?" "When business requirements change, what are the processes and costs of system expansion and adjustment?"

Asking to visit its operations center or communicate with existing customers, especially those in the same industry, is also a good way to get first-hand information. Listening to the actual problems encountered by other customers in project delivery and post-maintenance and their resolution processes is more convincing than any brochure.

All in all, introducing AI is a marathon, not a 100-meter sprint. Choosing a partner who not only starts quickly, but also provides supply, medical care and accompanying services throughout the journey is the most important guarantee for a company to successfully reach the intelligent destination. Putting the inspection of delivery and after-sales in advance is the most important insurance for investing in the long-term value of the project.