Changelog

Teammates can join your organization with their work email

Getting your team into Basedash no longer depends on sending every invite by hand. When a teammate signs up with a verified email at your company’s domain, Basedash now shows them a “Join your team” step with your organization, its name, and its member count. They can join in one click or create a separate organization instead. No more duplicate, empty workspaces from colleagues who signed up without an invite.

New organizations created with a work email have joining turned on by default, and you can turn it off during setup. For existing organizations, admins can turn it on from Members settings with “Allow anyone with a verified @yourdomain email to join”. People who join this way always start as members, personal email providers like Gmail and Outlook are never eligible, and anyone who was previously removed still needs a fresh invite.

Give every bar its own color

Single-series bar and funnel charts have a new “Vary colors by category” setting. Turn it on and each bar gets its own color, based on its category label. You don’t need a breakdown to get multiple colors anymore. Custom colors are saved against the category itself, so “Closed lost” stays red when filters change the numbers, and every teammate sees the same colors.

The AI assistant knows about the setting too. Ask it to color bars differently in chat, dashboards, insights, the chart editor, or over MCP, and it will use this option instead of a breakdown. We also fixed two related color issues: duplicating a dashboard, tab, or chart now keeps its custom colors, and automatic colors no longer reuse a color you’ve already picked for another bar.

Smarter, faster AI answers with GPT-6 Sol

Chat now runs on OpenAI’s newest model, GPT-6 Sol, by default. In our testing it gave noticeably more accurate answers to real analytics questions and responded about a third faster than the previous default. The lightweight AI that handles tasks like naming your chats now runs on GPT-6 Luna.

There’s nothing to configure. Chat, dashboards, and insights all pick up the new models automatically.

Fixes and improvements

• Added audit log entries for changes to organization AI context, AI skills, and data catalog descriptions, including edits made through the AI assistant or the public API.
• Showed the AI skills the assistant read in a chat’s sources, so you can check which instructions shaped an answer.
• Stopped source chips from linking to pages the viewer can’t open, such as admin-only settings or data pages inside an embed.
• Fixed favoriting dashboards in embedded Basedash, along with a case where a blocked action could leave embedded chat and dashboard edits stuck until the page was reloaded.
• Fixed chats that started with an attachment staying titled “New chat” instead of getting a descriptive name.
• Made chart and insight refreshes retry automatically when a Postgres read replica cancels a query, instead of leaving results stale.
• Fixed a blank screen some people saw when the app stalled while loading. Slow loads now explain what’s happening and offer a reload.
• Fixed the blurred page header in the iPhone Home Screen app on iOS 26.
• Centered the Hide schema icon in the data sidebar.
• Updated the “Continue with Google” button with Google’s current logo.

Build entire dashboards straight from chat

Chat can now do a lot more than answer questions and draft a single chart—it can build and edit whole dashboards for you. Describe what you want, and the assistant creates the dashboard, lays out the charts, adds tabs, and wires up variables and filters, all from plain language. As it works, it renders a live, interactive preview right inside the conversation, complete with tabs, filters, and real chart data, so you can see exactly what you’re getting before you ever leave chat.

Everything respects your existing permissions, and each dashboard the assistant builds is a real dashboard you can open and keep refining. When you’re chatting from Slack, dashboards come through as clean, named links so your team can jump straight to them in one click.

AI answers now use color to highlight what matters

AI-generated responses can now use semantic color to call out the important parts of an answer. Positive results, warnings, and problems render in green, amber, and red, so you can scan a response and immediately see what’s good, what needs attention, and what’s going wrong—instead of reading every line to find the signal.

The colors carry across the places AI shows up: chat, dashboards, charts, insights, and tasks. Answers delivered over email keep the same fixed colors, and in Slack they gracefully fall back to plain text so nothing ever looks broken.

Fixes and improvements

• Fixed scheduled insights that had silently stopped generating for some organizations, so recurring insights are flowing again.
• Fixed missing chart images in dashboard, automation, insight, and chat notifications, including cases where the dashboard’s original creator had left the organization.
• Fixed automation emails delivering without their charts, and made automation run API responses include chart metadata, including multi-source charts.
• Fixed slow and occasionally failing chart-image requests from the public API.
• Fixed Slack-created chats getting stuck on the “Slack conversation” placeholder—they’re now named automatically from the thread’s topic.
• Improved table charts so numbers, currency, and percentages right-align as a single clean value, keeping mixed columns lined up instead of scattered.
• Made table charts load more smoothly, automatically fetching the next rows as you reach the end of a long list.
• Added a thinking-step loading indicator to generating chats in the sidebar, so it’s clear which conversations are still working.
• Fixed pages, including login, breaking after a new release by automatically recovering when an old browser tab requests an outdated asset.
• Fixed an issue where creating a chart variable could fail when the request was retried.

Meet Models: a semantic workspace your whole team (and your AI) can build on

Definitions have grown up. They’re now Models—a top-level workspace that lives right below Data. A model is reusable, governed SQL that captures a core concept in your business, like your customers, orders, or active accounts, so everyone works from the same trusted definition instead of re-deriving it every time. You can reference a model directly in SQL like any other table with select * from models.<name>, and legacy definitions.<name> references migrate over automatically.

Models now carry real semantic meaning. Each one gets dedicated editor views for details, columns, measures, and segments, plus synonyms, a row grain, key columns, relationships, and plain-language usage guidance. The assistant reads all of that context when it answers questions—so it writes more accurate SQL, reaches for the right measures and filters, and stays consistent with how your team actually defines things. Admins who’d rather keep Models hidden can turn it off per organization in settings.

Basedash now speaks French, Spanish, and Portuguese

You can now use Basedash in English, Español, Français, or Português. Pick your language from profile settings and the interface switches instantly, with no page reload, so everyone on your team can work in the language they’re most comfortable in.

Language switching is fast and lightweight: only the language you select loads, so the app stays just as snappy no matter which one you pick.

Let your AI tools build charts and dashboards

Basedash’s MCP server can now do more than answer questions. Connected AI clients like Claude Code and Cursor can create and edit charts and dashboards directly in your workspace using plain-language instructions. Every created or updated artifact comes back with a durable Basedash link and chart screenshots, so you can jump straight from your AI tool into the real thing.

New read tools for listing and fetching charts and dashboards round out the workflow, and everything respects your existing access controls. Existing MCP connections pick up the new capabilities automatically—there’s no need to re-authorize.

Fixes and improvements

• Made the dashboards you’re actively viewing refresh faster by prioritizing your chart loads ahead of background refresh work.
• Added the underlying SQL and sources to every chart the assistant renders in an answer, including multi-source charts.
• Sped up chat answers so they appear as soon as they’re ready instead of waiting on source attribution to finish.
• Fixed automation creation so it no longer flashes a “not found” error, and allowed selecting a data-change trigger before its query is configured.
• Fixed chart edits failing to save on charts that have drill-downs configured.
• Fixed dragging a chart’s scrollbar accidentally moving the chart around the dashboard.
• Fixed data source deletion getting stuck on very large schemas.
• Fixed deleting a dashboard tab twice causing a sync error.
• Refreshed the login and sign-up screens.

See the sources behind every AI answer

When the assistant finishes answering, it no longer leaves a long, expandable trail of thinking steps and tool calls in your way. Completed answers now collapse that timeline into a simple “Analyzed for 1m 12s” summary, so the final response stays front and center. While it’s still working, you’ll continue to see the latest step it’s on.

Next to the copy and feedback buttons there’s a new Sources control. Expanding it shows exactly what the answer was built from—the tables, definitions, charts, data sources, read-only MCP connections, and web pages it drew on—alongside the queries it ran, each with the SQL and a preview of the rows it returned. Any action that changes something, like a mutating query, a new definition or automation, or an update to your AI context, now appears as a clear card beneath the answer and opens a details view when you click it, instead of being buried in inline callouts.

Fixes and improvements

• Improved the public automations API so a run’s details now return the rendered final answer with chart images.
• Made variable dropdowns with many options load smoothly by paginating them as you scroll, on dashboards, public dashboards, and variable configuration.
• Fixed cases where the schema browser and chat could keep showing stale tables after a database sync.
• Fixed the public AI usage endpoint returning an error for organizations on a shared billing account.