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Tell it what your columns mean once. Every answer after uses it.

We told Intellrise once what the columns in a 12,259-row sales dataset mean. Here is the SQL and charts it returned. Team: $100 a month, five seats.

Try it on your own data See the answers

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tables in the sample

12,259

rows of sample data

definitions saved

3 of 3

runs per question shown, same numbers

The semantic layer

What we told it, once

Saved on the data sources before the first question. Every question after starts from these — on Team, for all five seats in the workspace.

demo_orders.order_status

“One of paid, shipped, delivered, cancelled. Cancelled orders never happened — exclude them from any revenue figure.”

demo_payments.payment_status

“Always 'success': every row is money actually collected. Do not filter on it.”

Neither fact is visible in the column names. Asked the same questions without these two sentences, the AI counted cancelled orders as revenue (Selangor 114,376.00 instead of 109,983.14). With them, it never had to be reminded.

Question, the AI's SQL, the result

Ask in chat, get the query and the chart

gemini-3.5-flash-lite through Intellrise, 25 September 2026. Each query is copied character for character from what the AI wrote; each chart is drawn from the rows it returned.

Question 01

Which states bring in the most revenue?

Its plan: “Calculate total revenue by customer state, excluding cancelled orders, and show the top states.”

SQL written by gemini-3.5-flash-lite — verbatim

SELECT 
    c.state, 
    ROUND(SUM(o.total_amount)::DOUBLE, 2) AS total_revenue
FROM demo_orders_c66a5a o
JOIN demo_customers_7823ca c ON o.customer_id = c.customer_id
WHERE o.order_status != 'cancelled'
GROUP BY c.state
ORDER BY total_revenue DESC
LIMIT 10;

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 02

What are my top 10 products by revenue?

Its plan: “Calculate total revenue for the top 10 products by joining order items, orders, and products.”

SQL written by gemini-3.5-flash-lite — verbatim

SELECT 
    p.product_name,
    ROUND(SUM(oi.subtotal)::DOUBLE, 2) AS total_revenue
FROM demo_order_items_bbbf6d oi
JOIN demo_orders_c66a5a o ON oi.order_id = o.order_id
JOIN demo_products_62e2b1 p ON oi.product_id = p.product_id
WHERE o.order_status != 'cancelled'
GROUP BY p.product_name
ORDER BY total_revenue 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.

Both queries carry the cancelled-orders rule from the saved definition — WHERE o.order_status != 'cancelled' — without anyone mentioning it in the question. Each question was asked three times; all three runs returned these numbers.

The dataset

Five tables, one year of orders

Orders span 2024-01-01 to 2024-12-30. A synthetic sample generated for this page — the queries and results are real; the business is not. In the SQL above, each table name carries the six-character source id a workspace gives every upload (demo_orders_c66a5a).

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

Now teach it your own data.

Connect Postgres, MySQL, Redshift, a Google Sheet or a spreadsheet, save what your columns mean, and give five people the same answers. Team is $100 a month for five seats.

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