Why “simple” no longer cuts it in AI builds You used to get away with sticking to a single cloud Pick your poison—AWS, GCP, Azure—and stay there. The services were close enough. The trade-offs weren’t that serious But today? That’s a good way to get left behind AI models are improving weekly Certain models (like Gemini) are locked to specific clouds If you want the best, you’ve got to move fast—and be flexible That’s why we took a multi-cloud approach. It lets us use whatever tool is best, whenever it’s best. No more waiting for one provider to catch up Staying “cutting edge” isn’t a mindset. It’s an architecture decision