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app.anadock.com/storefront

Storefront

Admin

May 16, 00:00 – Aug 29, 23:59

Storefront performance across web, mobile, and retail channels.

Created Aug 12, 2026

Total Revenue

Total payment revenue collected within the selected date range.

$1,994,073

Total Units

Units shipped across all fulfilment hubs in the selected range.

22,350

Paying Customers

Distinct customers who made at least one paid order in the range.

5,726

Revenue Over Time

Payment revenue aggregated per week over the selected date range.

Revenue by Category

Share of payment revenue by product category in the selected range.

Top 5 of 16 categories

Total$2M16 categories

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.

Name

Production database

Type

Postgres

Host

db.example.com

Port

5432

Database

app_db

Username

app_user

Password

••••••••••

Use SSL

Add data source

Connecting...

Connected

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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 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.anadock.com/storefrontLive

Total Revenue

Payment revenue in the selected range.

$1,994,073

Total Units

Units shipped in the selected range.

22,350

Paying Customers

Distinct customers with a paid order.

5,726

Revenue Over Time

Payment revenue per week.

Units Shipped per Week

Volume shipped across the range.

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

Try it

SQL, charts, and layout, all from one prompt.

Operate

Don't just analyze. Act on it.

Select rows, run any action. Every run lands in Activity.

Pick rows. Run Custom Actions.

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.

idcustomer_nametotal_amountstatusActions

CC-101-431Marcus Reid$229.00pendingpending

CC-102-718Daniel Brooks$229.00pendingpending

CC-103-205Emily Carter$229.00pendingpending

CC-104-882Sarah Mitchell$199.00pendingpending

CC-105-339James Walker$229.00delivereddelivered

3 of 44 selected

Email sent for 3 rows. Result logged.

Every run lands in Activity.

app.example.com/activity

Activity

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

WhenActorActionDetails

Just now[email protected]Data source updatedAction "Send Email" on "Orders" (3 rows) — HTTP 200.

Sep 6, 2026, 5:33 AM[email protected]Data source updatedAction "Send Email" on "Orders" (1 row) — HTTP 200.

Sep 6, 2026, 5:34 AM[email protected]Data source updatedAction "Send Email" on "Orders" (5 rows) — HTTP 200.

Sep 6, 2026, 5:37 AM[email protected]Data source updatedRow deleted from "Orders".

Sep 6, 2026, 9:53 AM[email protected]KPI card updatedKPI card "Orders" was updated.

Sep 6, 2026, 12:43 PM[email protected]Business event addedBusiness event "Back-to-School 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

Every action leaves a trail.

Michael edited order #1234

Sofia 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 13 → Jul 25) directly on charts. Anomaly highlights are on the roadmap.

Summer Ad Campaign · Jun 13 → Jul 25

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.

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