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Medical Video Processing AI

Realtime video processing AI for identifying the crucial moments and Clinical View of Safety in a surgical setting. Artificial Intelligence is enhanced and deployed on the computer on wheels (CoW) hardware to assist surgeons during the operation.


We worked with the client to identify the best approach and tech stack. The state-of-the-art deep learning model and pipeline were explored to craft a future-proof solution.

Leveraged Specialized Expertise

Utilized the fundamental knowledge of computer vision and machine learning pipeline architecture to apply it to a surgical use case.

Modular Integration

The streaming pipeline supports variants of inputs and AI models to provide future-proof flexibility.

Performance & Accuracy Focused

Achieved low-latency with high accuracy, one of the biggest challenges in practically applying AI.


Curantis, Dallas, TX

Enabling real-time video processing AI for assisting laparoscopic cholecystectomy procedure on human patients.

  • Project/product mgmt.
  • Architecture
  • Development
Build Type
  • Greenfield
Tech Stack
  • NVidia DeepStream + Triton Inference Server
  • Jetson (Linux on ARM)
  • NVidia Clara AGX
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What We Did

Exploration & Planning

We worked with the client to:

  • Identify the suitable technology stack for low-latency and modular architecture to support multi-input, multi-model capability.
  • Plan for the development of the video streaming pipeline which will happen concurrently with the improvement of the deep learning AI.

Design & Development

Design and develop the pipeline for the continuous real-time execution AI on the provided CoW hardware. We then measured the baseline performance.

Plug & Play

Merge the pipeline with the deep learning models hosted on NVidia’s Triton Inference Server. The tuning and testing are supported to ensure that we satisfy the real-world usage requirements.

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