Tidepool is a product analytics platform designed to help businesses extract actionable insights from large-scale unstructured text data, such as chat conversations, user feedback, and LLM prompts. By leveraging advanced language models and embedding technologies, Tidepool enables users to analyze and categorize text data efficiently, facilitating better decision-making and enhanced customer satisfaction. Key Features and Functionality: - Attribute Creation: Users can define attributes by providing short text descriptions, representing specific questions or aspects they wish to explore within their data. - Category Discovery: Tidepool visualizes clusters within datasets, allowing users to inspect and create categories that they want to track, thereby organizing data more effectively. - Scalable Analysis: The platform employs lightweight embedding classifiers to efficiently categorize new data, scaling seamlessly to datasets containing billions of tokens. - Data Exploration: Users can explore the distribution of attributes and categories across entire datasets, chart correlations with business metrics, and delve into individual examples within each category. - Data Export: Tidepool allows for the export of enriched data into CSV files for ad-hoc analysis or writing back tables to data warehouses, ensuring integration with existing business intelligence stacks. Primary Value and Problem Solved: Tidepool addresses the challenge of deriving meaningful insights from vast amounts of unstructured text data, which traditional analytics tools often struggle with. By providing a no-code interface that is accessible to both technical analysts and non-technical stakeholders, Tidepool democratizes data analysis, enabling teams to uncover patterns, track trends, and make informed decisions that drive business success. Its ability to connect text data to key business metrics, such as revenue conversion and user segmentation, empowers organizations to identify opportunities for improvement and enhance overall performance.