Proven Across Industries

Challenge

The radiology department generates 2+ TB of CT/MRI data daily. They wanted AI-assisted diagnosis to improve reading efficiency, but patient imaging data must never leave the hospital network, and there was no dedicated AI ops team.

Solution

Deployed 1 Weisuan-B in the radiology server room, pre-loaded with lung nodule detection and fracture assessment AI models. Data flows entirely within the hospital. Doctors access AI annotations through the existing PACS system.

Challenge

Visual quality inspection relied on manual spot checks with ~3% miss rate, costing over ¥2M annually in returns. The company wanted AI visual inspection, but production line images contain core process parameters that cannot be uploaded to the cloud.

Solution

Deployed 1 Weisuan-B alongside the production line, connected to 4 industrial cameras running real-time defect detection. Each part is inspected in <200ms, with results fed directly to the MES system for automated rejection. All data stays within the factory.

Challenge

The bank needed anti-fraud and credit risk AI models, but financial regulations mandate that customer credit data and transaction records stay in-house. Traditional AI infrastructure would cost over ¥5M — far beyond a regional bank's budget.

Solution

Deployed 2 Weisuan-B units as a small AI cluster for real-time anti-fraud inference and batch credit scoring. Leasing model keeps monthly cost at ¥4,000 while meeting banking regulator data localization requirements.

Challenge

The municipal government was advancing smart government services involving highly sensitive citizen data (ID numbers, social security, property records). National regulations require all processing within local government cloud infrastructure.

Solution

Deployed 3 Weisuan-B units in the government cloud data center to support smart approval automation (OCR+NLP), 12345 hotline ticket classification, and urban management video AI analysis — all within the government private network.

Challenge

Wind farms are in remote mountainous areas, with each turbine generating 500+ MB of operational data daily. Transmitting data to headquarters for analysis was impractical due to bandwidth and latency. Unplanned turbine downtime costs tens of millions annually.

Solution

Deployed Weisuan-B at the wind farm substation as an edge AI node, running vibration analysis, temperature anomaly detection, and bearing wear prediction models locally. Only alerts and summary data are sent to headquarters, reducing bandwidth needs by 99%.

Challenge

A 10-person AIGC startup building automated marketing content generation. Public cloud GPU costs exceeded ¥80K/month with instability issues. Self-built infrastructure requires ¥1M+ upfront, but the team had limited funding.

Solution

Leased 2 Weisuan-B units at ¥4,000/month, deployed in their own office. Running Stable Diffusion and LLaMA fine-tuning. All data and model weights belong to the company — no cloud vendor lock-in.