Unlock the data advantage of high-performing generative models
Refine models faster with image data built for performance. High quality in, smarter results out.
From raw to refined
For AI leaders, product teams, and engineers aiming to boost model output, alignment, and time-to-value. Learn why scraped datasets and aesthetic proxies often fall short—and how Shutterstock’s Generative Score, clustering methods, and semantic evaluation framework provide a more reliable path to performance. You’ll uncover what makes a dataset truly “refinement-worthy,” how to balance quality with visual diversity, and how to evaluate model outputs using signals rooted in real-world user behavior.
Engineered for performance
- Accelerate model refinement with data grounded in real-world user behavior
- Reduce legal risk using fully licensed, ethically sourced image datasets
- Increase output reliability by aligning training data with generative preferences
- Boost creative diversity through strategic clustering and quality scoring
- Validate progress confidently with a robust evaluation framework
Download the guide to learn how our expertly curated datasets help your AI learn faster and perform better.
Download the guide today