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Connect your existing data and get a beautiful analytics + admin platform in minutes.

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app.example.com/overview
Jun 10, 01:17 - Sep 8, 01:17 Refresh all Add KPI card Rearrange

Total Revenue

Total Revenue

33,731.13

Orders

Total Orders

139

AOV

Average Order Value

242.67

Orders

Orders by Status Over Time

86420Jun 11Jun 19Jun 27Jul 5Jul 12Jul 20Jul 28Aug 5Aug 13Aug 21Aug 29Sep 7
CancelledDeliveredPending

Order Status

Orders by Status

Pending 49Delivered 56Cancelled 34

Live preview of a real customer dashboard

PostgreSQLMySQLSpreadsheetsREST APIsLogs & analytics · exampleMore databases · roadmap

Connect your data

Empty screen to live dashboard.

Connect your database, then build manually or let AI do it.

Connect your database.

app.example.com/data-sources/new

Add a data source

Connect an external database to this project. The connection is verified automatically when you save.

Production database
Postgres
db.example.com
5432
app_db
app_user
••••••••••
Use SSL
Add data source
Connecting...
Connected
Test connection

How would you like to build?

app.example.com/new-dashboard

Build manually

Choose charts, KPIs and tables yourself. Full control.

Generate with AI

Describe what to track — AI writes the queries and builds it.

This demo follows the AI path. Manual is always available.

This is the database of an ecommerce website. I want to track orders, revenue, AOV and repeat rate.

AI is working — one query per metric

Reading schema — found orders, customers, payments

-- revenue SELECT date, SUM(amount) FROM orders GROUP BY date;

-- orders SELECT date, COUNT(*) FROM orders GROUP BY date;

-- aov SELECT SUM(amount)/COUNT(*) FROM orders;

-- repeat rate SELECT repeat_buyers/total_buyers FROM customers;

4 queries written — picking line, pie and bar charts

Live dashboard, in seconds.

app.example.com/sales-overviewLive

Revenue

₹48,210

+18.2%

AOV

₹229

+4.1%

Repeat rate

32.4%

+2.0pts

Revenue trend

Last 30 days · live from orders

Orders per day

Bar view of the same query

Orders by status

Delivered62%
Pending28%
Cancelled10%

Auto-picked pie for breakdowns

Built from your data in minutes — edit any SQL, drag any widget.

Try it

Your dashboard, generated in seconds.

Operate

Do not just analyze. Act on it.

Select rows, run any action — every run lands in Activity.

Pick rows. Run Send Email.

app.example.com/orders

Orders

public.orders

Table settings
Columns Add row
Field contains ValueFilter
Action:----------GoSelect rows below, then choose an action and press Go.
id
CC-101-431pending
CC-102-718pending
CC-103-205cancelled
CC-104-882pending
CC-105-339delivered
3 of 44 selected

Run Send Email?

One HTTPS request will be sent with all 3 row(s). The HTTP result is logged. Choose a template to categorize this email dispatch.

Select Template

Order Status Update
Transactional
Payment Reminder
Finance
Delivery Notification
Logistics
Action: Send Email3 of 44 selected
CancelConfirm & sendSending…Sent
Email sent for 3 rows — result logged

Every run lands in Activity.

app.example.com/activity

Activity

Project events — latest 100 events. Only admins can see this page.

WhenDetails
Just nowAction "Send Email" on "Orders" (3 rows) — HTTP 200.
Sep 6, 2026, 5:33 AMAction "Send Email" on "Orders" (1 row) — HTTP 200.
Sep 6, 2026, 5:34 AMAction "Send Email" on "Orders" (5 rows) — HTTP 200.
Sep 6, 2026, 5:37 AMRow deleted from "Orders".
Sep 6, 2026, 9:53 AMKPI card "Orders" was updated.
Sep 6, 2026, 12:43 PMBusiness event "Monsoon Campaign" (2026-08-12 → 2026-09-30).

Developer control

AI writes the SQL. You stay in control.

Inspect it, modify it, ask AI to refine it. The query is never hidden.

revenue_overview.sql — AI generated, editable

You control the query
SELECT date_trunc('day', created_at) AS day,
SUM(amount) AS revenue, COUNT(*) AS orders,
SUM(amount) / NULLIF(COUNT(*),0) AS aov
FROM orders WHERE created_at > now() - interval '30 days'
GROUP BY 1 ORDER BY 1;

Audit logs

Serious enterprise accountability.

Rahul edited order #1234
Priya executed Send Email on 5 records
Alex: Pending → Delivered

Business context

Annotate what the numbers can't explain.

Mark events like Summer Ad Campaign (Jun 21 → Jul 12) directly on charts. Anomaly highlights are part of our vision.

Summer Ad Campaign — Jun 21 → Jul 12

Annotation

Shaded campaign window explains the revenue lift. No black-box anomaly claims — you annotate, the chart remembers.

FAQ

Questions, answered.

No. Connect your existing sources and build dashboards and admin views on top of the schema you already have.

Stop building internal tools from scratch.

It's already built. Connect your data and customize it.

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