The AI landscape is being reshaped by the rise of generative models capable of synthesizing high-quality data, such as text, images, music, and videos. The course toward democratization of AI helped to further popularize generative AI following the open-source releases for such foundation model families as BERT, T5, GPT, CLIP and, most recently, Stable Diffusion. Hundreds of software as a service (SaaS) applications are being developed around these pre-trained models, which are either directly served to end-customers, or fine-tuned first on a per-customer basis to generate personal and unique content (such as avatars, stylized photo edits, video game assets, domain-specific text, and more). With the pace of technological innovation and proliferation of novel use cases for generative AI, upcoming AI-native SaaS providers and startups in the B2C segment need to prepare for scale from day one, and aim to shorten their time-to-market by reducing operational overhead as much as possible.

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