Answer extracted from the The Josh Bersin Company podcast — listen to the full episode below.
How does Jupiter connect HR data to real business problems?
Jupiter embeds Galileo's intelligence directly into enterprise data systems like SAP, Oracle, and Workday, allowing users to ask business questions that automatically surface relevant human capital insights. The system chains business problems to HR solutions using the HR 2030 model, answering questions like "What is the span of control of our sales department?" and comparing compensation to market benchmarks.
Connecting Intelligence to Enterprise Data
Jupiter works by building a semantic layer that understands the data structures and terminology of major enterprise systems. When a user asks a business question—whether about organizational hierarchy, workforce planning, or pay equity—the system translates that inquiry into the underlying data models of Workday, SAP, or Oracle, then applies Galileo's knowledge base to deliver actionable answers.
The integration goes beyond simple data lookup. Jupiter maps business problems directly to functional HR capabilities, using the nearly 1,800 case studies and 95 functional capability areas that Bersin's company has documented over 30 years. This means the answer includes not just what your data shows, but context from similar companies facing the same challenge.
A Chain of Thought from Problem to Solution
The architecture creates what Bersin describes as a chain of thought connecting business problems to human capital issues, embedded in the HR 2030 model. This framework ensures that when someone asks about sales department efficiency, the system can identify whether the issue stems from span of control, leadership capability, compensation structure, or other structural factors—and suggest solutions based on what has worked in comparable organizations.
HiBob, Workday, ServiceNow, and other platforms are now integrating this layer. Users don't need to switch tools or navigate multiple systems—they simply ask their question in the platform they already use, and Jupiter surfaces the connected insights. As Bersin explains in this podcast episode, this shift was driven by customer demand: teams wanted Galileo integrated where they already work, not as a separate tool.
"We essentially built a new architecture that takes the essence of Galileo and carefully indexed it and tagged it in eight different dimensions so that the LLM can read it extremely well and does not have to hallucinate."
Josh Bersin — Founder and CEO, The Josh Bersin Company. For nearly 30 years, Bersin has led research into human capital practices across 95 functional capability areas, compiling nearly 1,800 case studies from organizations worldwide. His firm helps companies understand how to structure, develop, and manage their people in relation to measurable business outcomes.
The real advantage of Jupiter lies in its precision. The episode details how this multi-dimensional tagging prevents hallucination, ensuring that HR answers are grounded in both your company's actual data and validated research benchmarks from comparable organizations.
See also
What performance advantage does the optimized Agent Ready Corpus deliver compared to general-purpose language models?
The ARC corpus is 10 to 100 times more efficient at token usage for running complex HR questions compared to using ChatGPT or Claude alone.
What structural changes were made to optimize research content for AI consumption, and what is the Agent Ready Corpus?
The Josh Bersin Company restructured its content library to be AI-optimized, moving away from traditional book-style formats with introductions and tables of contents to create the Agent Ready Corpus—a carefully indexed and tagged knowledge base that allows language models to retrieve and apply research insights without hallucination.
Why did the strategy shift from building a specialized AI agent to creating a portable intelligence layer across multiple platforms?
Customers indicated they already had AI platforms like ChatGPT, Gemini, Claude, or Microsoft Copilot and wanted Galileo integrated there rather than as a standalone tool, driving the shift to a platform-agnostic approach.