Tree View is a Table section that allows App Admins to display work items in a structured, expandable hierarchy within a single table. It supports a top-down view of parent, child, and associated items, making it easier to understand how work is organized and connected across a solution. Column data…
10 January 2026 (Note: Official Release Notes are available as an attachment to this article.) Enhancements Dashboards: Copy Tab Notifications: Enhanced Email Format Shibumi AI: Launch Chatbot from the Navigation Sidebar Table: Tree View Issue Resolutions Export/Import section imports tiemout if too many calculations are impacted Update Favorites flyout when…
Overview The Heatmap chart provides a highly visual option for exploring program data. Enabling a method for quickly undertsanding intensity, concentration, or distribution across intersecting dimensions. When reviewing charts, you can: Hover over any cell in the chart to view the value and respective location on the gradient scale. Click…
13 December 2025 (Note: Official Release Notes are available as an attachment to this article.) Enhancements: AI Analyze: Ability to configure included Templates and Attributes AI Create Dashboard: Ability to add any data sets Audit Service: Default Values from Template and OOTB Attributes Business Rules: Ability to trigger a rule…
Overview On the Security Tab, App Admins can define who is able to modify Dashboards privacy settings. This limits the group of users who can make Dashboards ‘Public’, either All Users or App Admins.
Overview The Category Waterfall Chart visualizes positive and negative contributions to the toal value across defined categories, offering clearer insight into segment-level impact and composition. The following chart types are available in the Category Waterfall Chart: Build Up: Displays the increase & decrease in an Attribute or Record Count over…
The quality of an AI Agent’s output in Shibumi is directly shaped by the quality of its prompt. A well-crafted prompt provides clear context, leverages relevant data through injected expressions, and defines a structured, purposeful output. These elements help the AI understand what it’s analyzing, why it matters, and how…
The true power of AI Agents in Shibumi isn’t just in what they do — it’s in how they’re guided. Prompts act as the instruction set for the Agent, shaping the quality, consistency, and usefulness of every output. A well-crafted prompt can transform raw solution data into clear narratives, actionable…
AI Agents are a powerful way to unlock value from your solution — whether by generating insights, summarizing work, or automating routine analysis. But the quality of their output depends heavily on the quality of the prompt they’re given. A strong prompt acts like a well-written instruction: it clearly communicates…
15 November 2025 (Note: Official Release Notes are available as an attachment to this article.) Enhancements: App Administration: App Diferences App Administration: Publish Changed Templates App Administration: Attribute & Template Descriptions Charts: Category Waterfall Charts: Include Timeframe selection in Waterfall Y-Value configuration Dashboards: Guardrails over who can make a Dashboard…