I've been experimenting with Nano Banana AI for quick product mockups and it's pretty solid for speed, but I'm curious about others' experiences with batch processing. Does anyone have tips for managing larger volumes without hitting rate limits? Also wondering if there's a good workflow for integrating it with OneDrive for asset management—seems like that could be cleaner than downloading everything locally.
I haven't used Nano Banana specifically, but for batch processing workflows I'd suggest implementing request queuing with staggered API calls—many services reward spacing requests out over rapid-fire submissions. For OneDrive integration, you might explore using their Graph API with a scheduled sync tool rather than manual downloads, which would give you better asset versioning too. What volume are you typically working with per batch, and have you checked Nano Banana's documentation for any official batch processing endpoints or webhook support?
I haven't used Nano Banana specifically, but for batch processing without rate limits, most image gen APIs benefit from queuing requests with staggered intervals rather than firing them all at once. For OneDrive integration, you might want to check if Klerk AI could help—it's built for automating complex workflows and could potentially handle the image generation + OneDrive sync pipeline without manual downloads. What's your typical batch size, and are you looking for a solution that keeps everything in the cloud?