This automation aims to guide users through the process of data discovery and analysis, all the while maintaining the oversight of a data analyst. The company also highlighted that its generative AI model can mechanize numerous routine, low-value tasks inherent in the data analysis lifecycle. This approach, according to the company, enables human stakeholders to channel their energies toward transforming and documenting tables that require additional manual attention to ensure governance and trust in an AI-based workflow. “A simple prompt like ‘analyze trends in year-over-year sales growth by sales rep’ can yield a comprehensive presentation of pivotal insights and actionable steps.”įor human-AI collaboration, Rasgo said that its platform aids data teams by autonomously assessing tables in the data warehouse and discerning which tables are primed for intelligent reasoning and which need further refinement. Our intelligent reasoning establishes an ‘always-on’ virtual team of knowledge workers, consistently identifying business prospects and vulnerabilities,” said Parker. “We acknowledged the potential time constraints faced by humans in formulating all necessary inquiries. This equips enterprise data teams to accelerate analysis, as opposed to building queries and dashboards from the ground up. Parker stated that for intelligent reasoning, the platform trains GPT to replicate a data analyst’s role. Leveraging GPT-4 for intelligent business reasoning The platform also analyzes enterprise data continuously to provide trusted insights, enabling business users to make data-driven decisions without needing advanced SQL skills. “By combining the chat interface with our solution for intelligent reasoning, we aim to improve … operational efficiencies of key stakeholders while also trusting that AI is constantly analyzing data to derive key insights.”Īccording to the company, one of Rasgo AI’s key differentiators is AI Guardrails, which map data structures into familiar business terms, enhancing the efficiency and accuracy of data analysis while ensuring data security. Rasgo provides a metadata repository about the data to teach the AI how to make specific decisions when analyzing data so that it can iteratively improve and learn from human calibration,” Jared Parker, cofounder and CEO of Rasgo, told VentureBeat. “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.
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