Enterprise AI Agent Consulting and Custom Development

📌 Background

The AI agent market is projected to exceed 1 trillion RMB by 2026. However, most enterprises lack internal AI R&D and operations teams, making implementation services a critical necessity. Service provider Aijentra reports that its target clients are mid-to-large enterprises with 50 to 5,000 employees. These clients typically possess a digital foundation—such as CRM, ticketing systems, Feishu, or DingTalk—and prefer a phased, single-scenario implementation approach rather than deploying 10 agents simultaneously.

👤 Target Customers

Enterprise-level clients in sectors such as manufacturing, finance, and retail, with budgets managed by CIOs, digital transformation departments, or business line heads.

💰 Revenue Streams

1) Project-based consulting: Consulting and delivery fees charged per project, with an average contract value of over 100,000 RMB; 2) Ongoing maintenance subscription: Monthly maintenance fees charged post-delivery, approximately 20,000 RMB per month; 3) Performance-based commission: Commissions charged based on business performance improvements after successful deployment; 4) Training and knowledge base licensing: Fees charged per session or via annual license (an opportunistic revenue stream with no public figures available).

🧮 Cost Structure

· Labor costs for senior AI experts and industry consultants; · Large language model API usage fees and cloud computing resources; · Channel costs for project management, delivery, and post-launch operations.

🛡️ Moat

A standardized 4-week delivery process from assessment to production, expertise in vertical industry models, a knowledge base built from over 100 successful cases, and deep partnership resources with major cloud platforms.

🔑 Keys to Success

• Industry-vertical model construction
• Rapid PoC delivery mechanism
• Continuous maintenance and model iteration

⚠️ Risks

• Client churn due to project implementation failing to meet expected ROI
• Regulatory compliance risks in sectors like finance and pharmaceuticals
• Increased migration costs resulting from underlying large model upgrades

🏢 Cases

• Aijentra completed the deployment of an AI customer service agent for a manufacturing enterprise within 4 weeks
• Shushangyun provided an AI compliance review agent for a financial institution and implemented monthly operational services

📊 SWOT Analysis