As on-site and private cloud deployments continue to grow, organizations increasingly require large volumes of data to train their ML models. However, this data often contains a mix of genuine user traffic and bot-generated activity, which can reduce model accuracy and distort business insights.

We can leverage our Bot Defense capabilities to create a service that identifies and separates bot traffic from real user interactions. This would enable customers to train their AI/ML models using clean, high-quality human-generated data, while also gaining more accurate insights into real user behavior, preferences, and patterns to support better business growth decisions.