I am an AI Engineer, and I find synthetic data to be of great help, not as a replacement for real data, but to augment it.
It has always been useful for training, but for me, it has been especially useful for coming up with various scenarios to test different kinds of inputs. I believe synthetic data can be very helpful for evaluating agent traces and outputs, simulating different scenarios, and testing edge cases.
Quality > Quantity 🌱
Don’t spend your weekends manually collecting, cleaning, formatting, and expanding datasets for AI systems. DataCreator AI helps developers and AI teams generate high-quality synthetic datasets for training, fine-tuning, and evaluation workflows with continuous refinement, quality reviews, and diversity-focused data generation, so you can spend more time building models instead of preparing data.
