# ADR-005 — AI Model Strategy

## Status
Accepted for V1.

## Context
The vacancy emphasizes PyTorch, object detection, segmentation, and GeoAI. A portfolio build should show a real inference pipeline, not only AI text generation.

## Decision
Use Ultralytics YOLO as the first object detection runtime because it is practical, PyTorch-based, well documented, and fast to integrate. Add segmentation through YOLO-seg or SAM after the detection pipeline is reliable.

Model execution must be wrapped behind `ModelRegistryService` and `DetectionService` interfaces so the UI and API do not depend directly on Ultralytics internals.

## Consequences
GeoIntel can demonstrate model inference, georeferencing, output conversion, confidence thresholds, and QA/QC against GRB.

## Non-goals
Do not train a custom model in V1. Fine-tuning becomes V2/V3 after annotation and dataset export exist.