Automated data deliveryBeta
Raw data in.Ready reports out.
Pull from your database, warehouse, Airtable, Tableau, or Google marketing data, shape the exact table in chat, and deliver it to Sheets or a database table—on demand or on a schedule.
- 01Fresh sourcesGA4Search ConsolePostgreSQLMySQL
- 02Repeatable transformFilter rowsJoin sourcesCalculate metricsReplays every run
- 03Schedule
Every Monday
07:30 · EDT
Active - 04Monitored deliverySheetsSnowflakeBigQuery
SQL Server2,418 rowsDelivered
One deterministic run
Fresh input. The same logic. A recorded result.
A flow does not improvise. It pulls the source again, replays the saved transform, delivers the table, and records what happened.
- 01
Pull fresh data
Re-read GA4, Search Console, a Google Sheet, or a database query.
- 02
Replay the transform
Run the same filters, joins, aggregates, and calculated columns in the same order.
- 03
Write the result
Update or add, replace, or append rows in Google Sheets or a database table.
- 04
Record the outcome
Store status, rows written, duration, trigger, and any failure that needs attention.
Sources and destinations
Beyond Google. Start from the data you already have.
Combine marketing platforms, spreadsheets, and databases in one flow, then write the result where your team works.
Pull from
- Google Analytics 4
- Search Console
- Google Sheets
- Snowflake
- BigQuery
- PostgreSQL
- Supabase
- MySQL
- SQL Server
Airtable- Tableau
Deliver to
- Google Sheets
- Snowflake
- BigQuery
- PostgreSQL
- Supabase
- MySQL
- SQL Server
Every plan can deliver to Google Sheets. Database destinations are available on Max and Enterprise; Tableau sources deliver to Google Sheets.
Flow control
See the whole operation at a glance.
Destination, cadence, latest result, and current health stay visible in one operating view.
Transform layer
Not just moved. Prepared for use.
The data work completed in chat becomes a repeatable transform that runs the same way against fresh data.
Filter
Region, status, campaign, or any field
Join
Combine compatible sources into one table
Aggregate
Daily, weekly, region, or product summaries
Calculate
Margins, growth rates, ROAS, and custom metrics
Rolling windows
Re-center relative date ranges on every run
Scheduled outputs
Built around the reports teams already repeat.
Keep the useful routine. Remove the manual pull, spreadsheet cleanup, and copy-paste.
MARKETING / 07:30 MON
Cross-channel performance
GA4 + Search Console → Google Sheets
SEO / DAILY
Search history archive
Search Console → BigQuery
FINANCE / DAILY
Revenue and margin rollup
PostgreSQL → Google Sheets
WAREHOUSE / WEEKLY
Marketing data load
GA4 + Search Console → Snowflake
Run history and recovery
Know what ran—and what needs attention.
Every flow keeps an operational record, so failed delivery never disappears into the background.
Last run delivered
2,418 rows · 38 seconds
Next run scheduled
Monday at 07:30 EDT
Failure protection
Repeated failures pause the flow
Clear repair path
Reconnect, repair, then run again
Data Flows vs Scheduled Tasks
Deterministic delivery or scheduled AI work?
Data Flows re-pull fresh source data, replay the same transforms, and write to a destination. Scheduled Tasks schedule an AI agent's work instead.
Compare your options
Decide with evidence, not a sales pitch.
Open a neutral research prompt in the AI tool you already use. Compare capabilities, limitations, and fit before you choose.
AI answers can be incomplete. Check source links, current pricing, and product documentation before deciding.
Build your first flow. Run it when you need it.
Start free with manual, on-demand runs. Add scheduling when you move to a paid plan.