BuckVisionAI Hunting Intelligence
The plan should survive contact with the field.
Field Execution carries the saved hunting decision into a deliberate mobile workflow instead of forcing hunters to remember which stand, route or recommendation created the plan.
Verify → Start → Navigate
Before starting, the hunter verifies the relevant conditions. Start Hunt is deliberate. GPS guidance can update distance and bearing to the saved stand without silently persisting a breadcrumb history as part of the core Field Execution flow.
Arrive and check in deliberately
Arrival and check-in are explicit actions. BuckVisionAI does not auto-check-in because being physically near a stand is not the same as the hunter confirming that the hunt has begun there.
Hunt log and checkout
Field observations and notes can be added during the hunt. Checkout is explicit, creating a clean boundary between hunting activity and the outcome/learning phase.
Outcome returns to the right context
Outcome validation and controlled learning return to the same property, stand and hunt context. The purpose is to make the next hunting decision smarter without corrupting accepted property truth.