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Rasgo is a platform that enhances the capabilities of data warehouses using GPT-4, a powerful generative AI model. It is designed to elevate self-service analytics beyond traditional chat interfaces, providing businesses with a range of tools to make data-driven decisions more efficiently.

Key Features and Benefits of Rasgo:

  1. Natural Language Interaction: Rasgo allows users to query their Enterprise Data Warehouse (EDW) data using natural language, simplifying data analysis and visualization. This feature is particularly beneficial for users without extensive technical expertise in data querying​.
  • AI-Orchestrated Business Intelligence: The platform uses autonomous GPT-4-enabled agents to deliver insights directly from the EDW. This approach streamlines the process of data analysis and understanding, enabling businesses to quickly access critical insights​.
  • Customized GPT for Enterprise: Rasgo tailors the GPT model to suit enterprise needs by securely teaching it about specific data and Key Performance Indicators (KPIs), including visualizations. This customization provides businesses with tailored insights and rich business context​.
  • Secure Integration with EDW: The integration of GPT with EDW is handled securely, ensuring that raw data never leaves the EDW. Rasgo employs a semantic layer to facilitate interaction between the model and the EDW without copying any source data​​.
  • Proactive and Intelligent Insights: Rasgo aims to generate insights that create lasting intellectual value within an organization. Its generative insights empower teams to make smarter decisions and can reduce the time data teams spend creating knowledge products by up to 80%​.
  • Ongoing Development and Future Potential: Rasgo's current capabilities represent just the beginning of its potential. Future developments may include running enterprise simulations and planning with internal and external data sources.
  • Complex Reasoning and Autonomous Learning: GPT-4's ability to perform complex reasoning tasks and strategize based on dynamic objectives is leveraged by Rasgo. The platform uses autonomous agents guided by GPT-4 to pursue valuable analytical goals, seek novel information, and optimize other models​.
  • Adaptation to Enterprise Data Environments: Rasgo helps GPT-4 become robust against fluctuating states in enterprise data environments, a critical aspect of building a reliable enterprise AI system​

Additional Features:

  • Insight Refresh: Rasgo provides options for scheduling the refresh of AI-generated analyses, like inventory trend analyses, on a daily or weekly basis​.
  • Boards/Curation: It offers tools to organize generative insights by topics, tags, and data sources, facilitating easy curation tailored to team needs​​.
  • Insight Summary and Presentation: Insights generated by Rasgo can be auto-summarized and integrated into presentations, emails, or chats for effective sharing and collaboration​.
  • Transparent and Trusted AI: Each insight is backed by a SQL query, ensuring transparency in the insight generation process and allowing users to preview data for comprehensive understanding​​.
  • AI Manager: This feature enables teams to design workflows for AI agents, oversee their memory, and enhance their knowledge, ensuring alignment with specific organizational needs and goals​​.

Rasgo’s approach to integrating AI into business intelligence offers a unique blend of natural language processing, secure data handling, and intelligent, proactive insights. It positions itself as a powerful tool for businesses seeking to harness the full potential of their data with advanced AI capabilities.

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  • Enterprise AI
  • GPT4
  • Enterprise Analytics