“Those companies that wanted to use AI but were not allowed to, can finally do so now.”
# Those companies that wanted to use AI but were not allowed to, finally can now use it. ## Background: The awkwardness of AI transformation Recently, mainstream AI products such as ChatGPT, Claude, and Grok, along with their backend model API services, suddenly crashed, causing many individual and corporate users to be unable to log in and services to be interrupted. The industry generally believes that the root cause lies in large-scale failures in the infrastructure of cloud service providers like AWS. This exposes the real difficulties faced by many traditional companies eager to achieve “AI transformation”: large models and agents are popular, APIs are subscribed, and agents have been deployed, but it’s becoming increasingly troublesome. ## Three major pain points **First layer: Stability issues.** Complex business processes rely on cloud API-driven agents. Network fluctuations or cloud capacity limits can cause tasks to be interrupted, making it difficult to recover; everything has to start over. This is unacceptable for companies seeking a stable production environment. **Second layer: Cost issues.** Bosses encourage teams to use AI more, but when they do, they find that the costs are rising rapidly. Only…