Probably is a secure, local data agent that performs accurate data analysis using natural language queries. It connects to various data sources, including local files and major data warehouses, to explore and report quickly over billions of rows. This tool provides deterministically verified answers by refusing to guess, ensuring mathematical tasks are handled by a local, optimized compute engine while maintaining data privacy.
Funding
Funding not disclosed
Founders
Product
Problem
Generative AI products often produce inconsistent user experiences due to the stochastic nature of the underlying models. Traditional analytics methods often fail to capture the nuanced patterns in user behavior that drive satisfaction and retention in these AI-driven environments.
Solution
Patch provides a platform for visualizing and analyzing generative product data, enabling multi-dimensional evaluation of user satisfaction factors. By applying advanced statistical analysis, Patch helps businesses uncover hidden patterns in user behavior and optimize AI outputs to improve product performance. The platform identifies key factors driving user satisfaction, allowing teams to tailor AI outputs to user preferences and increase long-term engagement. This data-driven approach enables businesses to enhance customer experiences and drive revenue growth by understanding the impact of generative AI on user behavior.
Target Audience
Patch targets product teams, particularly those in the generative AI space, who need to understand and improve user satisfaction and retention.
Features
- Multi-dimensional analysis of user satisfaction factors in generative product data
- Identification of key factors driving user satisfaction
- Visualization of generative behavior to uncover hidden patterns
- Optimization of AI outputs based on data-driven insights