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Good embedded analytics is not just charts. It is governed metrics, transparent AI, and the platform controls that let you ship analytics to customers without losing sleep over consistency or cost.
Six updates are shipping now. They touch the chart editor, exports, the AI agent's transparency, the filter bar, database connections, and AI spend. Here is what changed, and why it matters if you are embedding Toucan in your product.
Charts
Chart operations, now in the semantic layer
The chart editor now runs on the semantic layer. That unlocks more calculations, custom formulas, and expressions directly where you build the chart, with no detour through a separate modeling step.
The point is not just more math. Because expressions resolve through the semantic layer, the numbers stay governed and consistent across every dashboard and every tenant. One definition, used everywhere.
Chart operations are rolling out behind a feature flag. To switch them on in your environment, set localStorage.setItem("ENABLE_SEMANTIC_CHARTS", "true") in your browser console.
Dashboard
Export any chart to CSV or XLS
You can now download the data behind any chart, straight from the dashboard, as CSV or XLS.
It is a small thing that closes a real gap: the people who need the numbers are not always the people logged into Toucan. Now your users can hand off a file without asking you to pull an export for them.
Filters, compact by default
The filter bar is now more compact and visually consistent with the rest of the interface. Less vertical space, same control.
On an embedded dashboard, every pixel you give back to the actual data is a pixel that makes the experience feel like part of your product, not a tool bolted on the side.
AI agent
Reasoning you can actually follow
The reasoning chain the agent shows after each answer is now structured and chronological. Every step and every tool it called, in order, with timing.
For an AI feature you are putting in front of customers, this is the difference between trust and a black box. When a user can see that the agent queried the semantic layer, ran a trend analysis, then wrote the answer, they believe the result. So do your support and sales teams when a customer asks how it works.
Platform
Database errors that explain themselves
for socket_addr db.acme-corp.io:28560
When a database connection fails, users now get a clear title, a plain-language explanation, and copyable technical details. No more deciphering a raw stack trace.
Connection issues are the most common snag when onboarding a new data source. A readable error turns a support ticket into a self-serve fix, which matters when your own customers are the ones connecting their databases.
AI credit limits per user
Org admins can now set a monthly AI credit cap per user. Full control over usage, with no billing surprises at the end of the month.
If you are embedding AI analytics across a base of customers, this is the cost guardrail you need: predictable spend per seat, set by you, independent of your billing cycle.
Ship analytics your customers actually use
All six updates are live. If you already embed Toucan, they are in your environment now.
If you are still weighing build versus buy for in-product analytics, here is the short version: Toucan is AI-native embedded analytics for SaaS products, multi-tenant by design, with your first dashboard shipping in days rather than quarters.
Alim Goulamhoussen
Alim is Head of Marketing at Toucan and a growth marketing expert with over 8 years of experience in the SaaS industry. Specialized in digital acquisition, conversion optimization, and scalable growth strategies, he helps businesses accelerate by combining data, content, and automation. On Toucan’s blog, Alim shares practical tips and proven strategies to help product, marketing, and sales teams turn data into actionable insights with embedded analytics. His goal: make data simple, accessible, and impactful to drive business performance.
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