QuaerisAI Embedded BI Analytics
Bring interactive analytics into your product without the time and effort of building BI.
- Queries run in your warehouse
- One certified definition per metric
- Cloud, on-premise or hybrid
Analytics That Feels Native.
Bring interactive reporting, dashboards, and insights directly into your application, so users get the data they need without leaving your product.
Every embedded deployment has three parts
- The surface
What the user sees
The board, chart, question box or narrative that appears in your product. It carries your layout and your theme, and it is the only part your users ever think about.
- The engine
What answers the question
The query layer that resolves what was asked against your data and the certified definition of each metric, so two surfaces asking the same question cannot come back with two numbers.
- The handoff
What makes it safe to expose
Your application tells the engine who is asking, and access is resolved for that identity at query time. This is the part that lets you put analytics in front of customers rather than only staff.
What it is not
Not a chart library
A charting package draws whatever you hand it. It has no opinion about where the numbers came from, whether they are the agreed ones, or who is allowed to see them.
Not a shared dashboard in a frame
Dropping one dashboard into a page gives every viewer the same dashboard. Embedded analytics resolves the view for the person looking at it, which is the part that takes real work.
Not a BI licence resold
Per-seat pricing collapses the moment your user count becomes your customers' user counts. Embedding is a different commercial shape, not a reseller agreement.
Analytics people can use without leaving their workspace
Embed a single component or the full experience. Each piece runs on the same metric logic and access rules as QuaerisAI itself.
Question bar
Let people ask questions in their own words and get a chart, a number and its source inside your app.
Dynamic dashboards
Replace fixed dashboards with boards that update with live data and change as the business does.
Stories and storybooks
Combine visuals, KPIs and commentary into narratives that refresh in one click, with no manual exports.
Shared threads
Discuss results in context. Share filters, pins and full stories with the right people.
Access rules
Each viewer sees only what their role allows, using the same rules they have in QuaerisAI.
Live data in place
Results come from your data where it lives. Nothing is extracted or synced into a separate copy.
Built for portals, apps and products
Internal portals and intranets
Give every team a place to ask questions and check performance inside the portal they open each morning.
Operational apps
Add analytics to CRM, ERP, field and service tools so people act on the numbers without switching screens.
Customer-facing products
Offer customers self-service analytics inside your product, and package advanced analytics as a premium tier.
Leadership reporting
Share stories and dashboards with executives and boards in the tools they already review.
From your data to your app in three steps
Connect your data
Point QuaerisAI at the warehouses and systems your teams rely on. Your data stays where it is.
Choose what to embed
Pick the question bar, a dashboard, a story or the full experience, and set who can see it.
Place it in your app
Add it to your portal or product. Viewers sign in through your app and see results scoped to their role.
Embedded, white label, headless.The difference is who owns the interface.
Our whole product, carrying your brand.
Our engine, none of our interface.
| Attribute | Embedded | White label | Headless |
|---|---|---|---|
| What you get | Views you drop into your app | A branded analytics product | Governed query interfaces |
| Who builds the interface | We do | We do | You do |
| Whose brand shows | Yours, around our views | Yours, everywhere | Only yours, there is nothing else to see |
| Time to first value | Fastest | Fast | Depends on your build |
| Engineering required | Integration work | Configuration | Front-end build, then maintenance |
| Design control | Themeable | Themeable | Total |
| Who asks the questions | Your users, in your product | Your clients, in their own workspace | Whatever you point at the layer |
| Non-visual consumers | Not the purpose | Not the purpose | First-class: agents, jobs, services |
| Semantic layer | Shared | Shared | Shared |
| Governance and lineage | Enforced at query time | Enforced at query time | Enforced at query time |
| Typical buyer | Product teams | Agencies, consultancies, vertical SaaS | Platform and data engineering teams |
Most teams end up mixing them
Embedded for the surfaces you would rather not build twice, headless for the one screen you care enough about to build yourself. The engine underneath does not change, so the numbers agree whichever route a given team took.
When embedded is the right choice,and when one of the other two is.
All three are our own products, so there is nothing to lose by saying which one you came for.
Choose embedded if
- You have a product with users in it today, and analytics is the gap
- You want analytics shipped in weeks rather than built over quarters
- Each of your customers needs their own data, isolated, without you writing that logic
- Our views, themed to match your product, are close enough to what you want
- You would rather spend your engineers on your product than on charts
Look at one of the others if
- Every pixel has to match a design system you already maintain
- The main consumer is not a person but an agent, a job or another service
- You are selling an analytics product in your own name, at your own prices
- There must be no trace of another vendor anywhere in the experience