A software development company expanded its AI feature rollout from 100,000 developers to 25 million in three months, highlighting the fascinating speed of scaling in AI.

A company scaled to $12 million in revenue within a year by switching models multiple times, demonstrating that enterprises care more about workflow efficiency than the specific AI model used.

AI's elasticity allows companies to scale operations quickly, enabling them to generate leads or complete tasks that previously required extensive hiring and staffing.

As companies scale their AI applications, it's crucial to find the optimal balance across quality, cost, and speed to achieve sustainable growth.

AI is driving unprecedented growth in startups, allowing small teams to achieve significant revenue milestones quickly, sometimes reaching $10 million a year within 12 months.

At Scale, we power the data infrastructure for the entire AI industry, with every major large language model built on top of our data engine, and we partner with enterprises and governments to implement this technology for their unique challenges.

American companies had to adapt quickly to scale AI inference after their previous providers' servers failed, leading to significant growth for Fireworks in capturing inference metrics.

We have developed a self-serve platform that allows developers to easily tune AI applications for speed and quality, facilitating rapid scaling and experimentation.

The initial business of Scale AI focused on generating data for self-driving car companies, which required us to stay ahead of AI trends.