Build trust in AI: According to a leading market intelligence firm, 80% of the data in the world is not governed. through AI/generative AI and other means, they assume very significant risks, including the possibility of compromising data security, privacy, and confidentiality, violating regulatory compliance norms, or feeding poor-quality training israel whatsapp number data data to algorithms to produce inaccurate, biased, or untrustworthy outcomes. Ungoverned data can also stifle growth and innovation. By ensuring adherence to trust, ethics, privacy, security, and regulatory requirements at scale, autonomous data management and fingerprinting build trust in AI, and also make the enterprise “data-ready” from an AI point of view.
Improve AI precision at scale: High-quality data is the critical factor for achieving high precision in AI models. As algorithms continue to evolve, their ability to recognize and understand even more complex data will continue to grow. This will open doors for even more groundbreaking applications of AI. SDF acts as the foundation that supports the advancements/complexities of the data exploration and enables the evolution of algorithms to unlock new possibilities in AI. With data fingerprinting, developers can define the data requirements based on the algorithm and progressively evolve the algorithm for a specific purpose.