Bloomberg introduced BQuant Assistant, a domain-grounded conversational AI coding assistant built into BQuant Desktop and BQuant Enterprise. Integrated within the BQuant development environment, BQuant Assistant gives financial professionals who are Bloomberg Terminal subscribers the ability to use natural-language prompts to write code, build dynamic applications, and accelerate financial data analysis workflows.
BQuant Assistant brings conversational AI directly into the same Python environment where users build investment strategies, dashboards, and quantitative financial analyses. BQuant Assistant can answer customers’ questions about BQuant, generate Python code, assist with querying Bloomberg’s vast datasets via Bloomberg Query Language (BQL), help users debug and iterate on their work, and build code for data visualizations. BQuant Assistant can also search the BQuant Help Center and draw from relevant example notebooks, libraries, and how-to guides when answering your questions. This grounding in the BQuant environment enables BQuant Assistant to generate context-aware responses about your projects, workflows and code, thereby providing more relevant support for financial data analysis than a general-purpose coding assistant.
BQuant Assistant can also respond with code suggestions and, subject to the user’s approval, insert and run code directly in their active project within the secure BQuant sandbox, so users can quickly move from question to result without switching context. Users retain full control over these actions because BQuant Assistant identifies the action it proposes and requests approval before reading from or writing to a notebook.
“Financial professionals are working with increasingly large and complex datasets, but turning an investment idea into a repeatable analysis can still require significant time and specialized coding knowledge,” said Shawn Edwards, Bloomberg’s Chief Technology Officer .
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