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Rasgo Unveils Rasgo AI: Elevating Data Analytics with Intelligent AI Reasoning

AI-powered analytics platform Rasgo has unveiled Rasgo AI, a self-service analytics solution that incorporates a GPT (generative pre-trained transformer) into enterprise data warehouse (EDW) environments. Unlike other GPT integrations focused on natural language chat interfaces, Rasgo’s AI distinguishes itself by employing GPT for “intelligent reasoning,” allowing it to function like a knowledgeable business analyst within data warehouses.

Rasgo’s objective is to alleviate knowledge workers from time-consuming, low-value tasks that hinder effective decision-making. By delegating these tasks to AI, Rasgo aims to empower these professionals to concentrate on strategic decision-making, leading to substantial improvements in overall enterprise value.

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Transforming Questions and Insights

Rasgo emphasizes that GPT-4 empowers the model to skillfully handle intricate reasoning tasks with evolving goals. This autonomous agent becomes proficient in generating a semantic understanding of EDW metadata, effectively educating GPT-4 about the data while maintaining data security within the enterprise’s protected environment.

Jared Parker, co-founder and CEO of Rasgo, stated, “One of our most exciting technical findings was that when provided with the right guidance, GPT-4 is not only good at answering data analysis questions but also good at asking them.” By coupling a chat interface with their solution for intelligent reasoning, Rasgo aims to enhance operational efficiencies for their customers’ key stakeholders, while also ensuring continuous AI-driven data analysis for deriving crucial insights.

A Key Differentiator: AI Guardrails Rasgo AI distinguishes itself with the introduction of AI Guardrails, which map data structures into familiar business terms, streamlining data analysis efficiency and precision while upholding data security. The platform operates by consistently analyzing enterprise data to provide reliable insights, allowing business users to make data-driven decisions without requiring advanced SQL expertise.

Empowering Intelligent Business Reasoning According to Parker, the platform’s approach to intelligent reasoning involves training GPT to replicate the role of a data analyst. This equips enterprise data teams to expedite analysis rather than constructing queries and dashboards from scratch. The platform establishes a continuous virtual team of knowledgeable workers, identifying business opportunities and vulnerabilities.

Human-AI Collaboration

Rasgo’s platform supports data teams by autonomously assessing data warehouse tables, identifying which ones are suited for intelligent reasoning and which necessitate further refinement. This approach enables human stakeholders to concentrate on transforming and documenting tables requiring manual attention, ensuring governance and trust within an AI-driven workflow.

Automating Data Analysis

Rasgo’s generative AI model automates multiple routine, low-value tasks inherent in the data analysis lifecycle, guiding users through the data discovery and analysis process while maintaining oversight akin to a data analyst. The platform’s ultimate goal is to enhance accuracy and instill trust in organizational processes.

Navigating Databases with GPT-4

To navigate databases, Rasgo’s AI model creates embeddings for all data warehouse metadata and user-provided instructional data. These embeddings are utilized within the ReAct (reason + act) AI workflow, allowing swift retrieval. The model autonomously refreshes these embeddings as new tables emerge, schemas evolve, or fresh user instructions are incorporated.

Responsible AI Development

Parker emphasizes the importance of collaborative efforts between humans and AI to ensure responsible AI development and desired outcomes. Explicit rules, instructions, and guardrails are set to ensure trust and safety, especially in the context of enterprise data. The platform incorporates an “AI Manager” capability to mitigate risks and disparities.

Privacy and Security Measures

To address data privacy and security concerns, Rasgo employs “push down compute” capabilities, ensuring generated SQL remains within the organization’s cloud data warehouse environment without exposing raw data.

Strategic Partnerships

Rasgo recently partnered with Snowflake’s Partner Network to enhance the benefits of the Snowflake Data Cloud. Through this collaboration, Rasgo leverages GPT for intelligent reasoning, streamlining self-service analytics. The company envisions expanding such partnerships to cater to diverse organizational needs throughout their data analytics and AI journeys.