Rasgo
Rasgo Overview
Rasgo is a revolutionary self-service analytics tool that leverages the power of Generative Pre-trained Transformer 4 (GPT-4) to provide businesses with intelligent insights and data-driven decision-making capabilities. It offers a secure and efficient way to analyze Enterprise Data Warehouse (EDW) data, with the AI model being taught about your data and Key Performance Indicators (KPIs) for tailored insights and rich business context. The tool also features autonomous GPT 4-enabled agents that deliver insights straight from your EDW, and every AI-enabled interaction is logged and discoverable in the application. Rasgo is trusted by major companies and is geared towards creating lasting intellectual value within an organization.
Rasgo Highlights
- Rasgo uses GPT-4 to perform complex reasoning tasks, strategize based on rewards, break down objectives into tactics, and more. It's a self-learning and self-teaching AI that can manage itself and its tasks.
- The tool ensures that your raw data never leaves your EDW. It uses a GPT-powered semantic layer to translate between the model and your EDW without copying any source data.
- Rasgo is designed to be proactive and always-on, seeking out valuable insights and interacting with users to optimize for high-value analytical work. It aims to reduce the time your data team spends creating knowledge products by 80%.
Use Cases
A business uses Rasgo to analyze their EDW data and gain intelligent insights. The AI model is taught about the business's data and KPIs, providing tailored insights and rich business context. This allows the business to make data-driven decisions.
The business is able to make more informed decisions based on the insights provided by Rasgo. This leads to improved business performance and increased profitability.
A company uses Rasgo to analyze their raw data without it leaving their EDW. The tool uses a GPT-powered semantic layer to translate between the model and the EDW, ensuring the security of the data.
The company is able to analyze their data securely, without the risk of data breaches. This increases the company's trust in the tool and allows them to use it more extensively.
A data team uses Rasgo to optimize their work. The tool is proactive and always-on, seeking out valuable insights and interacting with users to optimize for high-value analytical work. This reduces the time the data team spends creating knowledge products.
The data team is able to create knowledge products more efficiently, reducing their workload by 80%. This allows them to focus on other important tasks and increases their productivity.