University AI Teaching Environment Solution
New · AI-Integrated Product · An integrated AI teaching solution for university computer labs
Based on the vDisk Cloud Desktop Centralized Management Platform, AI capabilities are embedded into existing lab infrastructure: no additional GPU servers need to be purchased by the school. By connecting uniformly to domestic commercial large-model APIs, combined with image marketplace batch deployment, an OpenAI-compatible gateway, a teaching network drive, and timetable/IoT integration, a "ready-to-use" AI teaching environment is achieved.
Producer: Shanghai Chengcheng Information Technology Co., Ltd. (Wedie vDisk)
This document is a solution overview. Specific features and pricing are subject to commercial and delivery agreements. For user operation details, see the vDisk User Manual.
Solution Highlights (Summary)
| Dimension | Description |
|---|---|
| Cost approach | No self-built large models or heavy-asset GPU clusters — connect uniformly to commercial APIs, with usage and permission control managed by the platform |
| Additional hardware | Compared to the "self-built GPU server per lab" approach, this solution emphasizes a 0 additional GPU server deployment path (subject to actual procurement and contract) |
| Model compatibility | Supports DeepSeek, ERNIE Bot, Tongyi, Zhipu GLM, Doubao, iFlytek Spark, Tencent Hunyuan, Kimi, and more (updated based on commercial integrations) |
| Teaching loop | Image marketplace + vDisk network drive (virtual disk) + Token usage tracking and limits + conversation archiving for session continuity |
What is the vDisk AI Teaching Environment Solution?
The vDisk AI Teaching Environment Solution embeds large-model invocation capabilities into the vDisk Cloud Desktop Centralized Management Platform: administrators can select or deploy images with pre-integrated AI teaching components via the image marketplace, enabling batch deployment with consistent versions. The platform provides an OpenAI API-compatible proxy, so VS Code, Cursor, common plugins, and in-house software can all connect to domestic large models through a unified protocol.
Students can complete learning and programming tasks inside the cloud desktop; combined with AI vision and IoT capabilities, classroom patrol, alerting, and timetable integration can be realized. The AI Teaching Space is paired with a vDisk network drive: mounted as a virtual disk (e.g., D:, NTFS), AI outputs and user directories are stored on the server side, supporting session continuity and helping to save Tokens (reducing repeated long context submissions).
Why Is Self-Building a "Full-Spec" AI Server Often Unsuitable for Universities?
Taking full-capability DeepSeek-R1 (671B scale) as an example: industry sources commonly indicate that multiple high-end GPUs are required, and the total cost can reach several million RMB per unit. Beyond the price, institutions typically also face:
- Budget: Educational users have limited budgets; heavy-asset procurement is difficult to approve
- Maintenance and tuning: These are research-oriented capabilities with high operational costs for everyday teaching
- Iteration: Commercial models iterate quickly; self-built stacks can face constant upgrade pressure
- Compliance: Providing generative AI services externally often involves licensing and compliance processes
The vDisk solution rationale: Rather than building models in-house, connect uniformly to mature commercial AI APIs on the market, and complete cost control, permission allocation, and usage tracking on the vDisk side, allowing schools to use leading model capabilities at a manageable cost.
Self-Built AI Server vs. vDisk AI Teaching Platform (Comparison)
| Comparison Dimension | Self-Built AI Server (Typical Heavy-Asset Approach) | vDisk AI Teaching Platform (API + Centralized Management) |
|---|---|---|
| Initial hardware cost | Commonly cited as the 200–300 million RMB/unit range (varies by configuration) | Under the 0 additional GPU server approach, incremental hardware cost approaches 0 (subject to contract) |
| Deployment timeline | Often measured in months | Approximately 4 steps to connect (see below) |
| Model updates | Often dependent on hardware and stack upgrades | Admin switches backend model; frontend continues through the same OpenAI-compatible entry point |
| Day-to-day O&M | Often requires dedicated AI/system engineers | Can integrate with the existing lab O&M system |
| Student experience | Multiple independent environments and configuration items | Boot-and-use, unified account and gateway configuration |
Four Solution Modules
Module 01 · AI Teaching Space
- Image Marketplace: Select or deploy images with pre-integrated AI clients, teaching environments, and dependencies to minimize per-machine installation and version drift.
- OpenAI-Compatible Interface: Exposes a proxy endpoint compatible with OpenAI; VS Code, Cursor, JetBrains plugins, domestic coding assistants, and in-house programs connect via a unified gateway + key configuration.
- Ready to Use: AI clients can be placed on student desktops; with unified authorization, model capabilities are available from the moment the machine boots.
- Token Control: Tracks consumption per student, allows individual limits, and provides cost transparency.
- Conversation History Archiving: Supports loading context in the next session to save Tokens and allows teachers to review the process.
- Specialized Knowledge Base (Optional): Customizable knowledge bases by department or major, with responses tailored to institutional context.
- Flexible Model Switching: Switch backend providers from the admin panel — the frontend protocol remains unchanged.
vDisk Network Drive (Teaching Network Drive — Important)
- Form: Not a web-based drive, not FTP, and not a regular Windows shared folder — it is a virtual disk mount at the same level as the system disk (displayed as a local drive letter in "This PC").
- Write and Redirection: After mounting with account credentials via the campus network, writes are directed to the server; Desktop, Documents, AppData, and other folders can be redirected to the network drive, realizing "what you see is what is saved."
- AI Integration: Content generated by the model is stored on the network drive, enabling session continuity in the next class and reducing repeated long-context submissions.
- Security Boundary: Data is generally accessed in a closed loop on teaching terminals with the vDisk client deployed (specific policy subject to deployment configuration).
Module 02 · AI Teaching Assistant Space (Vision & Timetable)
Leveraging existing surveillance cameras for AI visual analysis (the claim of no additional hardware required is subject to the specific project):
- Classroom Patrol: Records classroom conditions during class hours; can retain recordings strategically during non-class hours.
- Safety Inspection: Detects personnel loitering, suspicious objects, and other risk indicators, pushing alerts to WeChat Official Account / admin panel, supporting a 7×24 monitoring approach.
- Equipment Inspection: IoT device statuses are consolidated on a large-screen dashboard.
- Timetable Integration: Mandatory patrol when no class is scheduled; automatic shutdown of computers/air conditioning/lighting/access control after class ends; pre-warming and automatic power-on/door opening before class starts.
Module 03 · Unified IoT Device Management
Surveillance cameras, access control, air conditioning, lighting, and other systems are brought into the same vDisk platform and can be operated from both the PC console and WeChat Mini Program, reducing the need to switch between multiple systems:
- Surveillance: Multi-channel preview, image rotation, extension to Mini Program.
- Access Control: Remote open/close, timetable integration.
- AC/Lighting Control: One-click and automatic timetable-based strategies for energy savings.
Module 04 · Cloud AI Computer Lab (IDV/Cache Architecture)
- Concept: There is no need to equip each student machine with a GPU; the platform provides AI runtime environment images and distribution uniformly; combined with IDV local caching, environments start in seconds and the impact of network jitter is reduced.
- Multi-Campus: Supports unified image maintenance across multiple campuses (actual cases and network conditions subject to the project).
Applicable scenarios: Computer/AI lab courses, AI general education courses, smart lab security, automated O&M power control, multi-campus unified management, AI teaching introduction at budget-limited institutions, etc.
AI Teaching Space Connection Process (Four Steps)
Image and Network Drive Ready
Select/deploy images with integrated AI components from the image marketplace; complete network drive account setup, drive letter assignment, and Desktop/Documents/AppData redirection to ensure AI outputs and materials are saved in real time and continuity is available for the next session.Connect to Large Model and OpenAI-Compatible Gateway
Configure the domestic model and gateway from the admin panel, exposing an OpenAI-compatible address for all software to invoke uniformly.Bind to vDisk User System
Model authorization is bound to student accounts — upon login, the user receives a Token quota without requiring teachers or students to register with individual vendors.Start Teaching
Students open the desktop or any software configured with the gateway to begin using it; the backend tracks usage and supports quota policies.
Related Products
| Product | Description |
|---|---|
| vDisk Cloud Desktop Centralized Management Platform | IDV/VOI cloud desktop · IoT · Operations automation — User Manual |
| cc-class Electronic Classroom Software | Screen broadcasting · 4K broadcasting · No distinction between teacher/student terminals |
| cc-LIMS Lab Management Platform | Equipment reservation · Hazardous chemical management · AI safety inspection, etc. |
Contact Us · Custom Solutions & Quotes
- Email: aaron@newvhd.com
- WeChat: okstop88
- Online Support: Enterprise WeChat Customer Service
- Company: Shanghai Chengcheng Information Technology Co., Ltd.
- ICP Filing: 沪ICP备2024076873号-2
We welcome inquiries for custom solutions and quotes tailored to your institution's lab environment, or to schedule a case study presentation and demo session.