The strength of Datahunt is that it provides quality data from well-trained data labelers and competent project managers.
I'm always pleased with not only the project design, but the quality we were able to achieve with AI-assisted labeling.
AI-powered automation, human cross-labeling, and secondary and tertiary verification resulted in more accurate and high-quality data.
I was able to resolve various requirement modifications issues that arose during the project through efficient communication.
Only 1% of all AI is data-centric, not 99% model-centric, and that 1% is driving progress.
Only 15% of all AI is applied to real-world industries due to low-quality data.
80% of the AI lifecycle is data processing. If it fails, it's a huge waste of time and money.