Blog Insights
Technical Insights and Industry Perspectives
Sharing our practical experience and forward-looking insights in AI, automation, and software development
Defining AI Project Acceptance Criteria: Functionality, Performance, and Security Are All Essential
AI project acceptance is far more complex than traditional software acceptance. This article provides a complete AI project acceptance criteria template covering four dimensions: functionality, performance, security, and outcomes.
7 Pitfalls in AI Project Delivery: Why 80% of AI Projects Fail to Launch Successfully
AI project delivery is fundamentally different from traditional software projects. This article analyzes 7 common pitfalls and response strategies to help AI projects move successfully from demo to production.
Hybrid Cloud AI Architecture: Best Practices for Keeping Core Data On-Premises and Moving General Capabilities to the Cloud
Analyze the design principles of hybrid cloud AI architecture, including data classification, model layering, and traffic routing, to help enterprises balance security and cost.
A Complete Guide to Private Deployment of Large Models: 7 Steps from Model Selection to Production
A detailed guide on how enterprises can select open-source large models, evaluate computing requirements, and deploy inference services to achieve private AI capabilities that keep data inside the corporate network.
Integrating AI Capabilities into CRM Systems: From Customer Insights to Intelligent Recommendations
Practical experience integrating AI capabilities into Salesforce and self-built CRM systems, including complete technical solutions for scenarios such as automated customer profile generation, sales script recommendations, and churn alerts.
AI Compute Cost Optimization: 5 Strategies to Increase GPU Utilization to Over 80%
GPUs are the largest cost item in AI operations. This article shares five proven compute optimization strategies to help enterprises significantly reduce costs without compromising results.