Hasty was launched during a company-wide hackathon at wattx. The team faced challenges with existing tools to prepare data sets that were time-consuming and inefficient. Hasty's goal was to make the execution and implementation of Vision AI projects technically possible, easier and more cost-effective.
✕ Time-consuming annotation
Manual data labeling is slow and inefficient.
✕ Inconsistent qualityHuman errors affect the accuracy of flagged data.
✕ Many use cases require internal experts with limited availability
This can create bottlenecks as experts often have to perform multiple tasks simultaneously, reducing the company's efficiency and responsiveness.