Databricks launches compound AI-powered business intelligence solution

Data and AI company, Databricks, has launched Databricks AI/BI, a new type of business intelligence (BI) product that aims to democratise analytics and insights for anyone in an organisation.

Databricks AI/BI features Dashboards, an AI-powered, low-code interface for creating and distributing fast, interactive dashboards and Genie, a conversational interface for addressing ad-hoc and follow-up questions through natural language.

Both are powered by a compound AI system that continuously learns from usage across an organisation’s entire data stack, including ETL pipelines, lineage, and other queries. According to the company, This allows AI/BI to answer complex questions accurately and automatically, without the requirement for upfront setup or modeling associated with conventional tools.

Ali Ghodsi, Co-founder and CEO at Databricks, said, “A truly intelligent BI solution needs to understand the unique semantics and nuances of a business to effectively answer questions for business users. We believe this requires a different approach than how BI software has been designed in the past, one that places an AI system at the center of the architecture and is designed to take advantage of the AI systems’ strengths as well as complementing their weaknesses to tackle the challenges of understanding and learning these nuances. The launch of AI/BI is a step towards building such a system.”

Databricks is the Data and AI company with more than 10,000 organizations worldwide including Block, Comcast, Condé Nast, Rivian, Shell. The company stated that AI/BI’s intelligence is enabled by the Databricks Data Intelligence Platform, which is natively integrated to provide unified governance, lineage, secure sharing, and lightning-fast performance for all data sizes.

AI/BI uses a compound AI system that utilizes an ensemble of AI agents to reason about business questions and generate useful answers. Each agent is responsible for a narrow, but important task, such as planning, SQL generation, explanation, visualization and result certification. The system is also designed to continuously learn and improve its performance based on human feedback.

Inputs form bl intern Vidushi Nautiyal