Live demo

See what Intellrise returns, before you sign up.

Four charts built on a 12,259-row synthetic e-commerce dataset. Every chart below shows the exact SQL it runs and the exact numbers it returns. No account, no AI key, no mockups.

Connect your own database See the dataset

tables, queried with joins

12,259

rows of sample data

pre-built charts

signups required

The dataset

Five tables, one year of orders

Orders span 2024-01-01 to 2024-12-30. This is a synthetic sample dataset generated for demonstration — not a customer's data. The queries and results are real; the business is not.

Table	Rows	What it holds
demo_orders	3,000	One row per customer order: order date, customer, payment method, status, shipping fee, discount and total amount.
demo_order_items	5,494	Line items — one row per product within an order, with unit price, quantity and subtotal.
demo_payments	2,845	Payments collected against orders: amount, settlement date, status and channel.
demo_customers	800	Customer directory, including the state each customer is in.
demo_products	120	Product catalogue with category, brand and unit cost price.
Total	12,259

Cancelled orders are excluded

Order status is one of paid, shipped, delivered, cancelled. Every query on this page filters out cancelled orders, so nothing below counts revenue that never happened.

Dates arrive as text, so the SQL casts them

The CSV loader does not parse dates, so date columns land as text. Intellrise records that in the source's schema notes, which is why the first query casts to TIMESTAMP before calling strftime instead of failing on a type error.

Question, query, result

The four charts, end to end

Each block is one pinned chart from the demo dashboard: the question it answers, the SQL it runs, and the values it returns.

This is the query the chart runs, with one cosmetic difference: each CSV source registers in DuckDB under a generated alias, so in your own workspace `demo_orders` appears as `demo_orders_` plus a six-character source id.

Question 01

How did revenue move month by month in 2024?

Pinned on the demo dashboard as Monthly revenue trend

SQL executed

SELECT strftime(CAST(o.order_date AS TIMESTAMP), '%Y-%m') AS order_month,
       ROUND(SUM(o.total_amount), 2) AS revenue
FROM demo_orders o
WHERE o.order_status <> 'cancelled'
GROUP BY 1
ORDER BY 1
LIMIT 24

Monthly revenue trend

Drawn from the query result above

Scroll the chart sideways to see every bar. Month against revenue. Amounts are unitless in the sample data.

Revenue holds a narrow band across the year: February is the low month at 37,714.84 and September the high at 53,445.30 — about 42% above it. No month runs away from the rest.

Question 02

Which states bring in the most revenue?

Pinned on the demo dashboard as Revenue by state

SQL executed

SELECT c.state AS state,
       ROUND(SUM(o.total_amount), 2) AS revenue
FROM demo_orders o
JOIN demo_customers c ON c.customer_id = o.customer_id
WHERE o.order_status <> 'cancelled'
GROUP BY 1
ORDER BY 2 DESC
LIMIT 20

Revenue by state

Drawn from the query result above

Scroll the chart sideways to see every bar. State against revenue. Amounts are unitless in the sample data.

Six states appear in the sample. Selangor leads at 109,983.14 and Sabah trails at 78,134.42; no single state accounts for more than a fifth of the year's revenue.

Question 03

What are my top 10 products by revenue?

Pinned on the demo dashboard as Top 10 products by revenue

SQL executed

SELECT p.product_name AS product,
       ROUND(SUM(oi.subtotal), 2) AS revenue
FROM demo_order_items oi
JOIN demo_products p ON p.product_id = oi.product_id
JOIN demo_orders o ON o.order_id = oi.order_id
WHERE o.order_status <> 'cancelled'
GROUP BY p.product_id, p.product_name
ORDER BY 2 DESC
LIMIT 10

Top 10 products by revenue

Drawn from the query result above

Scroll the chart sideways to see every bar. Product against revenue. Amounts are unitless in the sample data.

The leader, Action Camera 4K, contributes 11,680.75 — about 2% of the year's line-item revenue. This catalogue spreads revenue widely rather than concentrating it in a few products.

Question 04

How much have we actually collected, split by payment channel?

Pinned on the demo dashboard as Collected revenue by payment channel

SQL executed

SELECT pm.channel AS payment_channel,
       ROUND(SUM(pm.amount), 2) AS collected_revenue
FROM demo_payments pm
JOIN demo_orders o ON o.order_id = pm.order_id
WHERE pm.payment_status = 'success' AND o.order_status <> 'cancelled'
GROUP BY 1
ORDER BY 2 DESC
LIMIT 10

Collected revenue by payment channel

Drawn from the query result above

Scroll the chart sideways to see every bar. Payment channel against collected revenue. Amounts are unitless in the sample data.

Collection is close to even across the four channels: COD 148,596.42 and FPX 148,352.19 are within 250 of each other, with Credit Card lowest at 135,130.85.

Straight answers

What this page is, and what it isn't

What it is

Static output from real queries. The SQL shown is the SQL each chart runs, and the values are what it returned against the committed sample CSVs.
Proof the dashboard path needs no AI model: those charts render for an account with no AI provider key at all.

What it isn't

Not a live query console. This page is pre-rendered HTML; it does not connect to a database and you cannot type a question into it.
Not AI-written SQL. These four queries were written by hand for this page. In the product you ask in plain English and Intellrise writes the SQL, runs it and charts the result — that is a different path from the one shown here.
Not real customer data. It is a synthetic sample dataset, and the amounts carry no currency unit.

To ask your own questions of your own database, you need an account and your own AI provider key. Intellrise is bring-your-own-key on every plan, so AI usage is billed by your provider, at your provider's rates, under your control. This page needs neither — it is static output, so you can judge the SQL and the charts before creating anything.

Questions about this demo

Do I need an account to see these charts?

No. This page is static HTML built from query results — there is no login, no form and no AI key involved in viewing it.

Is this real customer data?

No. It is a synthetic sample e-commerce dataset generated for this page. The queries and the results are real; the underlying business is not.

Can I load this dataset into Intellrise?

No — Intellrise connects to data you already have. There is no sample dataset to import: you point it at your own Postgres, MySQL, SQL Server, Redshift, BigQuery, Snowflake or Databricks, or upload a CSV or Excel file, or connect a Google Sheet. This page exists so you can judge the output before doing any of that.

Do I need an AI provider key to use Intellrise?

Yes. Intellrise runs on your own provider key — Gemini, OpenAI, Anthropic, DeepSeek or MiniMax — so the questions you ask go through your own account rather than ours. This page needs no key because it is static HTML built from results we ran in advance.

Why are the amounts shown without a currency?

The sample dataset stores amounts as plain numbers with no currency unit recorded, so labelling them with a currency symbol would be inventing information the data does not contain.

Why do the queries cast dates before formatting them?

CSV sources load without date parsing, so date columns arrive as text. Intellrise records that in the source's schema notes, so the SQL casts to TIMESTAMP before calling strftime instead of failing on a type error.

Now point it at your own data.

Intellrise connects to the database you already run — Postgres, MySQL, SQL Server, Redshift, BigQuery, Snowflake, Databricks — or to a CSV, an Excel file or a Google Sheet. It runs on your own AI provider key, so the questions go through your account, not ours.

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