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 Qrvey

Multi-tenant analytics automation for SaaS vendors.

Qrvey markets heavily to SaaS vendors embedding analytics. The platform bundles data workflows, visualization, and tenant-oriented packaging so teams can standardize on one vendor for customer 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	Qrvey	QueryPanel
In-app experience for end users	Packaged SaaS analytics may rely on hosted embed surfaces or iframe-oriented patterns for part of the customer UI.	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.
Platform shape	Bundled analytics platform aimed at SaaS embedding use cases.	Focused toolkit: React embeds + AI generation + optional headless `ask()` on your API, on top of your databases.
Trainable knowledge & steering	Knowledge is bundled with the vendor’s analytics pipeline; fine-grained SQL exemplars and column-level business notes next to your repo are less of a first-class workflow.	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).
Data plane	Often includes hosted components for parts of the analytics pipeline.	Designed so customer data stays in infrastructure you control; QueryPanel does not store warehouse passwords.
Customization	Configuration inside the vendor platform and standard embed patterns.	Code-adjacent: `@querypanel/react-sdk` for the dashboard shell, `@querypanel/node-sdk` in your middleware for signing and queries.
AI workflow	Varies; evaluate current product docs for NL and automation coverage.	Natural language is the default input for new charts in the embedded experience.
Best first win	Standardize a single embedded vendor for many customer tenants.	Prove NL→SQL + one embedded dashboard in a single product area, then expand.

When Qrvey is the better fit

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

You want a packaged embedded analytics suite with less custom glue between data prep and UI.
You prefer a vendor-managed path for parts of the analytics data plane.
You value automation-oriented features across the embedded lifecycle.

When QueryPanel is the better fit

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 the customer UI as real React (`@querypanel/react-sdk`)—not a hosted iframe shell—while keeping SQL execution and credentials on your servers.
You want SQL generation and execution clearly separated: you run queries; QueryPanel never needs your warehouse passwords.
You are optimizing for a developer-first integration: React in the browser, Node SDK in API routes, your auth model.
You want AI-native flows (question → SQL → chart) wired directly into your product screens.

Still evaluating Qrvey and QueryPanel?

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

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