Artificial Intelligence
NeuroMetrics - Real-Time AI Inference Pipeline
Duration: 4 Months
Stack: Next.js, Python, PyTorch, Docker, GCP
The Challenge
An institutional medical research group needed to run low-latency AI image analysis, but their existing Python backend experienced timeouts and high memory leakage under concurrent diagnostic image uploads.
Our Solution
We developed a task-distributed pipeline containerized with Docker, routing analysis jobs to custom GPU clusters. Next.js serves the frontend client interface, retrieving processed diagnostics asynchronously via WebSockets.
Key Outcomes
- Lowered image processing time by 75% (down from 28s to 7s)
- Stabilized memory leakages via automated thread termination runbooks
- Automated HIPAA-compliant diagnostic reports generation
Key Deliverables
- WebSocket live progress inference tracker
- 3D medical image rendering viewer on modern browsers
- Encrypted diagnostic archive vault