What's New

Reusable Library is coming to Reporting — browse and insert shared components directly in the dashboard editor, no need to switch to Development.

Previously, using library blocks required switching to Development, which added friction and completely blocked explorers. With this update, you can insert existing library components right where you work. Blocks built by one team member are instantly available to everyone.

Learn more: Reusable Components

Timeline​

Expected by end of March 2026.

In complex data models, users can create metric breakdowns that are technically valid but analytically wrong.

These queries run successfully and return plausible numbers, but the results are meaningless. This silent failure undermines trust and hurts self-service.

Now you can control which dimensions can be used with each metric using the filter_direction property on relationships.

Why this matters​

• Prevents silent data correctness issues before they reach end users
• Turns semantic correctness into a default behavior, not a best practice
• Keeps self-service powerful and safe, even in multi-fact (galaxy) schemas
• Reduces the need for manual user education or tribal knowledge

📚 Learn more​

• Controlling which dimensions can be used with a metric: Detailed walkthrough with examples
• Controlling filter and grouping paths: Reference documentation for filter_direction

As-Code Color Palettes lets you define and manage color palettes directly in AML, alongside your data models.

Previously, color palettes were managed through Admin Settings with no version control or easy way to reuse them consistently. Now you can:

• Define categorical, sequential, and diverging palettes in AML and reference them at the project, theme, or chart level — changes propagate automatically everywhere a palette is referenced
• Map specific data values to specific colors (e.g., "Vietnam" always yellow, "US" always red) and have every chart that displays those values automatically use the correct color, no per-chart configuration needed

Set workspace-wide defaults so new dashboards inherit your brand colors automatically.

Timeline​

This feature is currently in development and expected to be available in July 2026.

AI Development Copilot is now in beta. Analysts can ask the copilot to build datasets, wire up dashboards, or edit any code file in Development — without leaving the editor.

Previously, building out a semantic layer meant hand-writing AML file by file. The copilot takes care of the repetitive parts: scaffolding models and datasets, adding relationships, translating a sketch into a canvas dashboard, or refactoring a messy field definition. You stay in charge — review the diff, tweak, commit.

Learn more: Build datasets with AI

AI-powered Dashboard Summaries will automatically generate and save a short narrative alongside your dashboard — highlighting key trends, notable changes, and actionable insights.

Stakeholders who don't have time to interpret every chart get the story at a glance. Dashboard owners get a consistent written summary that updates with the data, instead of writing one by hand each reporting cycle.

Local Development with AI Agents will let you use the AI tools you already know — Claude Code, Cursor, GitHub Copilot — alongside Holistics through MCP.

Local agents bring richer development tooling: git actions, diffs, auto-complete, and inline code suggestions. Pair that with Holistics' semantic layer via MCP and you get a modeling workflow that stays connected to governed data while feeling like the code editor you're used to.

OAuth for MCP Server will let you connect web-based AI agents — like Claude.ai or ChatGPT — to the Holistics MCP Server without manual token setup.

Today, connecting to MCP means generating an API token, copying it into a JSON config, and wiring endpoints by hand. OAuth collapses that into a one-click flow, so non-technical users can get their own AI agent talking to Holistics without IT involvement.

Organization-level AI Memory will let admins promote useful insights from individual users' AI memory up to the organization level — surfacing suggestions to improve the semantic layer and dashboards based on real usage patterns.

Today, AI memory is per-user: what one analyst teaches the AI stays with that analyst. Promoting it org-wide means the whole team benefits. Over time, AI gets smarter for everyone, grounded in how your organization actually analyzes data.

AI Usage Analytics will give admins visibility into AI adoption across the organization: who is using AI, what types of questions get asked, and how usage trends over time.

This helps you measure ROI, identify training opportunities, and understand which teams get the most out of AI — so you can double down where it's working and unblock teams where it isn't.

Embed Events lets you control embedded Holistics dashboards from your application using JavaScript. Send commands, listen for user interactions, and keep your app and dashboard in sync — all through the browser's standard postMessage API.

Previously, embedded dashboards were one-directional — your app could configure the embed at load time but couldn't respond to user interactions or send commands afterwards. With Embed Events you can:

• Sync filters — push filter values from your app into the dashboard, or listen for user filter changes and reflect them in your app
• Navigate dashboards — build a custom tab switcher or menu that controls the iframe without a full reload
• React to errors — detect embed_error events and auto-refresh an expired JWT to keep the session alive

Learn more: App & Embed Communication