AI-Driven Construction Cost Precision Control SaaS
1) Traditional cost software licenses and annual subscriptions; cloud-based value-added services for AI cost calculation
Key Fields
FIELD STAMPS📌 Background
In 2026, Glodon moves into a dual-wheel phase of digital construction and AI-driven operations, shifting from selling software to providing data-driven cost precision services. According to the company's 2025 annual report, full-year operating revenue reached 6.068 billion yuan, with net profit attributable to shareholders of 405 million yuan, a year-on-year increase of 61.77%. Among this, digital cost business revenue was 4.779 billion yuan, accounting for nearly 80%, and the gross profit margin rose to 58.33%, an increase of over 22 percentage points compared to the previous year.
👤 Target Customers
General construction contractors, project owners, cost consulting agencies, and government-funded project entities
💰 Revenue Streams
1) Traditional cost software licenses and annual subscriptions; cloud-based value-added services for AI cost calculation and change early warning billed by project scale; BIM data collaboration platform seat subscription fees; 2) Cost training: structured hands-on quantity takeoff training and advanced feature courses charged per term for construction enterprise cost teams; 3) Private deployment: lump-sum implementation fees for localized deployment and integration with existing cost systems for large construction enterprises and government-funded project owners.
🧮 Cost Structure
AI R&D and computing power investments, BIM engine and lightweight platform maintenance, and nationwide sales and implementation network costs
🛡️ Moat
AI training corpus barriers formed by two decades of accumulated construction cost industry data, switching costs for design institutes and general contractor clients, and a nationwide implementation service network
🔑 Keys to Success
- Deep integration of AI models with industry cost data
- Transitioning from a tool-based to a platform-based subscription model
- Scaling up after validating return on investment through pilot benchmark projects
⚠️ Risks
- Construction industry cyclical fluctuations compressing client budgets
- AI product commercialization progress falling short of expectations
🏢 Cases
- Glodon
📊 SWOT Analysis
Strengths
- Leading market share in domestic cost software with a massive client base
- Deep synergy between AI and existing cost data creating differentiation
Weaknesses
- Revenue under pressure during cyclical downturns with heavy transformation investments
- AI commercialization monetization pace and profitability still awaiting validation
Opportunities
- Affordable housing and urban renewal projects releasing incremental demand
- AI data-driven cost precision providing new pricing space for cost consulting upgrades
Threats
- Open-source and cloud-based competitors eroding the long tail amid domestic substitution
- Real estate and infrastructure cyclical fluctuations transmitting to SaaS renewal rates