Data quality platform Anomalo unveils AI-powered unstructured text monitoring at Data + AI Summit 2024.

Anomalo has enhanced its data quality platform to include unstructured text monitoring, addressing the need for high-quality data in GenAI applications. Unstructured data, making up 90% of enterprise data, poses challenges due to its inconsistent, error-prone nature. These issues are critical when such data is used in GenAI models, which demand high accuracy and security.

Anomalo’s new feature, currently in private beta, enables companies to evaluate and organize large amounts of unstructured text, pinpointing issues such as duplicates, sensitive information, and abusive language. This capability ensures only high-quality data feeds into GenAI models, improving their performance and reducing privacy risks.

Elliot Shmukler, CEO of Anomalo, highlights that data quality is pivotal for effective GenAI applications. The new tool helps data teams quickly evaluate and rectify unstructured data, ensuring optimal model performance and compliance.

Sid Stephens, a representative from a major quick-service restaurant company, acknowledges that Anomalo’s platform efficiently identifies and resolves data quality issues, which are crucial for data-driven projects. This advancement in unstructured text monitoring supports the growing integration of GenAI in enterprise operations.