A comprehensive toolkit for standardizing, processing, embedding, and retrieving data for AI applications.
Import data from various sources including JSON, CSV, databases, and web content with standardized preprocessing.
Create high-quality vector embeddings from text using state-of-the-art models with batching and caching.
Store and retrieve embeddings efficiently with support for FAISS and in-memory databases optimized for similarity search.
Identify and mask personally identifiable information with customizable detection rules and anonymization methods.
Validate data quality with schema verification, content validation, and detailed quality reports.
Improve results over time with user feedback, drift detection, and continuous quality monitoring.