Querypanel - 2026 Pricing, Features, Reviews & Alternatives

QueryPanel is AI-native analytics infrastructure for B2B SaaS teams that need customer-facing dashboards, not another standalone BI tool for internal analysts.

Most SaaS products eventually become their customers' reporting engine. Teams start with a few charts, then discover they also need auth, multi-tenant isolation, a query API, chart generation, a dashboard builder, and ongoing maintenance. That accidental second product eats roadmap for quarters. QueryPanel replaces it with installable infrastructure: connect your database, embed an AI analytics workspace, and let users ask questions in plain language.

The problem QueryPanel solves

Customer-facing analytics is different from internal BI. Your users expect insights inside your product, scoped to their account, styled like your UI, not a separate login to a warehouse tool. DIY paths (Metabase forks, custom Vega apps, bolted-on chat-to-SQL) usually fail on tenancy, UX, or both. QueryPanel is built for that product-native, multi-tenant path from day one.

How it works

Connect your database (PostgreSQL, ClickHouse, BigQuery, or MySQL) and sync schema.

Embed the React workspace or call the headless Node SDK from your backend.

Users ask in plain language. QueryPanel retrieves relevant schema and training context, generates parameterized SQL with a clear rationale, and produces a matching chart.

Dashboards stay live in your product, same session, same shell, tenant-scoped by design.

What's included

Headful React SDK: Embed a Notion-like dashboard workspace and AI assistant with QuerypanelEmbedded. White-label UI, slash commands, and per-tenant dashboard forks so customers customize analytics without leaving your app.

Headless Node SDK: Use qp.ask() when you need full UI control or a zero-trust architecture. QueryPanel generates schema-grounded SQL; you execute it where you already run queries. Credentials and result sets stay in your environment, we don't store customer database passwords for the headless path.

Natural language to SQL and charts: One pipeline from question to insight: intent, retrieval, generation, reflection, tenant verification, and visualization. Answers are grounded in your schema, not generic LLM guesses.

Multi-tenant isolation by design: Tenant context travels with the request. JWTs are verified server-side. Isolation is part of SQL generation and execution, not a UI filter someone can forget. Built so customer dashboards never leak across accounts.

Trainable knowledge base: Improve accuracy with gold SQL examples, glossary terms, column/table annotations, and tenant context. The system gets better for your domain over time.

MCP, BYOK, and enterprise controls: Governed analytics workflows for AI agents, bring-your-own-key, and enterprise options including bring-your-own-model.

Who it's for

Product, platform, and engineering leaders at multi-tenant B2B SaaS companies shipping premium analytics tiers, self-serve reporting, or embedded dashboards. Best fit when you want a product-native React experience first, with an optional headless SDK for custom UIs and stricter data control.

What QueryPanel is not

It is not a warehouse BI portal for analysts, not a generic chat widget bolted onto charts, and not a replacement for your database. It is infrastructure for embedding tenant-safe analytics where your users already work.

Stop paying roadmap interest on DIY analytics. Ship customer-facing insights in days, not another quarter of building the wrong product.