What this means in practice

  • Mount a camera above a lane cows already use, with steady lighting and a way to read each cow ID
  • Have a trained scorer score a set of cows so the model has scored images to learn from
  • Suggest a score for each cow and list those whose score has changed or sits outside the target range
  • Have a trained scorer check flagged cows in person and record the final score
  • Add newly scored images back into training each season and whenever the herd or setup changes

How Lid Vizion approaches it

We start with the business decision and operating context, define ownership and measurable milestones, then use configuration, integrations, automation, or custom software only where each earns its place.