Industrial AI Video Analytics Implementation
Budget: $250 – $750 USD
Xenon Consulting partners with fast-growing manufacturers that want to move from ad-hoc practices to data-driven discipline. Right now the single, most urgent piece is an ML model that turns raw video streams from the shop floor into actionable insights. By integrating this AI layer we intend to optimise day-to-day operations and give plant managers the evidence they need to tighten quality, safety and throughput.
Here is what the engagement covers:
• Build or adapt a computer-vision model that can ingest live or recorded footage, detect predefined events and generate analytics dashboards or API outputs that slot neatly into existing systems.
• Guide the full AI integration cycle—data collection, model training, validation, deployment and monitoring—so the solution stays accurate as conditions change.
• Transfer knowledge to our internal team, including concise documentation and a hand-over session, ensuring we can maintain and scale the model independently.
Success means the video analytics run in real time (or near real time), maintain consistent accuracy on the agreed metrics and are stable enough for continuous plant use without manual babysitting.
If you have proven experience in computer vision, deep learning frameworks such as PyTorch or TensorFlow and a practical mindset for deploying models in industrial environments, your expertise will make an immediate impact.
Here is what the engagement covers:
• Build or adapt a computer-vision model that can ingest live or recorded footage, detect predefined events and generate analytics dashboards or API outputs that slot neatly into existing systems.
• Guide the full AI integration cycle—data collection, model training, validation, deployment and monitoring—so the solution stays accurate as conditions change.
• Transfer knowledge to our internal team, including concise documentation and a hand-over session, ensuring we can maintain and scale the model independently.
Success means the video analytics run in real time (or near real time), maintain consistent accuracy on the agreed metrics and are stable enough for continuous plant use without manual babysitting.
If you have proven experience in computer vision, deep learning frameworks such as PyTorch or TensorFlow and a practical mindset for deploying models in industrial environments, your expertise will make an immediate impact.