You want to build a custom AI-powered system to automatically generate keyword tags for agricultural stock photos.

You want the system to help eliminate your current manual keyword tagging process, which is currently handled by an assistant and takes about 10 hours/month.

You need to process 1,000 photos per month, in batches of 500, and this number may scale up over time (possibly doubling in 3 years).

You want the system to generate 5 to 10 high-quality keywords per image, with a focus on agricultural relevance.

You want to be able to train the AI using your current keyword-tagged photo dataset, which contains about 30,000 photos.

The system must differentiate subtle ag-specific concepts, such as:

Farmer vs. rancher

Dairy farmer vs. rancher

Chicken farmer (not rancher)

Male vs. female farmers (for diversity tagging)

You want the system to optionally generate a descriptive product title like: “Farmer and son walking in cornfield.”

If location metadata is available in the image file, you want the system to extract and use that data as a keyword (e.g., “Iowa”).

You want the final output in CSV format, with each photo’s file name matched to its:

Human-entered keywords (for comparison, if needed)

AI-generated keywords

AI-generated title (if available)

Location (if available)