QueryPanel is the embedded analytics platform for multi-tenant SaaS. Primary product: a headful React SDK (Notion-like dashboards and AI assistant). Secondary: a headless Node SDK for zero-trust custom UI. Searches that look like “fury query panel” almost always mean QueryPanel.

Is this another BI tool?

QueryPanel is infrastructure for embedding analytics and generating safe SQL, built for product surfaces, not standalone analyst workspaces.

How do you handle tenant isolation?

Tenant context is part of generation and execution, not something you toggle later in a dashboard filter.

What does implementation look like?

Attach your database with the SDK, wire auth claims, and embed UI where customers already work. Scope follows your surfaces, not building a query engine from scratch.

How do you keep AI SQL accurate as schemas evolve?

Ground generation in synced schema metadata and your knowledge base (annotations, glossaries, and examples) so retrieval and SQL stay aligned with how your data model actually works.

How are tenants counted?

A tenant represents a distinct customer or organization within your SaaS product. We count the number of unique tenants that access or generate analytics in a given billing month.

What counts as an AI chart?

An AI chart is generated whenever an end-user asks a natural language question that results in a new chart, or when an editor uses AI to create or modify a dashboard block.

What happens when limits are exceeded?

You can purchase overage credits for AI charts. For tenant limits, we'll notify you when you approach your plan's limit and help you upgrade to the next tier. We never cut off access for your end-users without warning.

How are AI models selected?

We support OpenAI, Gemini, Anthropic, and even OpenRouter. Bring-your-own-key is available from Starter and above (including Growth and Scale). Custom plans also support bring-your-own-model setups. If you want a specific provider or model path, ping us at csaba.ivancza@querypanel.io.

QueryPanel vs Metabase

Open-source analytics with straightforward embedding for lighter customer-facing dashboards.

Metabase is a popular open-source analytics tool for internal dashboards that also supports embedding into customer-facing products. Teams often shortlist it when cost, self-hosting control, and a familiar question/dashboard workflow matter more than product-native React UX or deep multi-tenant AI analytics.

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Comparison at a glance

This table summarizes typical positioning. Every vendor changes over time—validate details against current documentation and your security review.

Dimension	Metabase	QueryPanel
In-app experience for end users	Metabase embedding typically delivers Metabase questions, dashboards, or interactive embeds inside your product; polish and theming depend on embedding mode and configuration.	First-class `@querypanel/react-sdk` components—`QuerypanelEmbedded` for a full dashboard, or `QueryPanelProvider` with `QueryInput` / `QueryResult` for a bespoke flow. They render in your React tree like any other product screen (layout, router, modals, tokens)—not a separate iframe "mini app" on another origin. Mint short-lived JWTs on your server; never ship your workspace private key to the browser.
Primary product shape	Open-source / self-host or cloud analytics platform oriented around questions, dashboards, and collections—often used for internal BI with optional embedding.	Headful React workspace plus headless Node `ask()` calls designed for customer-facing SaaS analytics first.
Trainable knowledge & steering	Correctness usually comes from curated questions, models, and how your team documents the database—not a productized gold-SQL / glossary / tenant-definition loop tied to NL→SQL.	Gold SQL queries (curated examples the model prioritizes), database annotations (business context on tables/columns, re-embedded with schema), glossary (domain terms and definitions), and tenant-level definitions (isolation field, enforcement, and per-tenant sync context so every ask() is grounded in the right customer slice—not a one-size global prompt).
Natural language workflow	Metabase is strongest as a dashboard and question tool; AI depth is limited relative to AI-first embedded analytics platforms.	Natural language to SQL and chart generation are central paths for both embedded users and server-side SDK calls.
Developer ownership	High control when self-hosting; embedding and multi-tenant permission design are largely your team's responsibility.	Product engineering embeds React components and calls `ask()` from API routes while reusing application auth and drivers.
Multi-tenant SaaS fit	Achievable with careful permissions, sandboxes, or row-level configuration; buyers should validate external-customer isolation end to end.	Tenant id and isolation metadata are part of the embedded JWT and query-generation contract.
Best first win	Stand up dashboards quickly on a familiar open-source stack and embed a lighter reporting surface for early customers.	Launch tenant-scoped AI analytics inside your React product without treating Metabase as the long-term customer UX shell.

Open-source flexibility versus embedded product UX

Metabase is attractive for teams that can own hosting, permissions, and the customer experience around its dashboards. QueryPanel is aimed at SaaS teams that want tenant-aware customer questions and dashboard customization to feel native to the product from the first release.

When Metabase is the better fit

Honest tradeoffs help your team pick faster—and match how buyers actually decide.

You need a lower-cost or open-source starting point for dashboards and light embedding.
Internal analytics and simple customer reporting can share the same Metabase deployment model.
Your team is comfortable configuring embedding, permissions, and multi-tenancy manually rather than buying a SaaS-native embedded suite.
Advanced AI-assisted dashboard customization is not the primary customer job yet.

When QueryPanel is the better fit

Choose QueryPanel when customer-facing AI analytics and a React-native product experience are the requirement; choose Metabase when cost, self-hosting, and a familiar dashboard tool are the priority.

You want a trainable knowledge system—gold queries, DB annotations, glossary, and tenant-aware definitions—so NL→SQL and charts reflect your business, not generic schema-only guesses.
You want customer analytics to feel like a native React product surface with a Notion-like workspace and built-in AI assistant—not a Metabase UI framed inside your app.
You need tenant-aware natural-language SQL generation as a first-class product workflow, not a bolt-on question builder.
You want a headless zero-trust path where your backend owns JWT signing and SQL execution for customer asks.
Multi-tenant isolation, white-label polish, and customer self-serve customization are core product requirements from day one.

Comparison FAQ

Is Metabase or QueryPanel better for multi-tenant SaaS analytics?

Metabase can work when your team is prepared to configure and operate its embedding and permission model. QueryPanel is a stronger fit when tenant-aware AI SQL and a React-native customer workspace are core product requirements.

Still evaluating Metabase and QueryPanel?

Start on the free tier, embed one dashboard, and compare implementation time against your current shortlist.

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