Automated data delivery

Raw data in.
Ready reports out.

Pull from your database, warehouse, Airtable, Tableau, or Google marketing data (Meta Ads coming soon), shape the exact table in chat, and deliver it to Sheets or a database table—on demand or on a schedule.

Pipeline ready
FLOW-04
  1. 01Fresh sources
    GA4
    Search Console
    Google Ads
    PostgreSQL
  2. 02Repeatable transform
    Filter rows
    Join sources
    Calculate metrics
    Replays every run
  3. 03Schedule

    Every Monday

    07:30 · EDT

    Active
  4. 04Monitored delivery
    Sheets
    Snowflake
    BigQuery
    SQL Server
    2,418 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.

  1. 01

    Pull fresh data

    Re-read GA4, Search Console, Google Ads, a Google Sheet, or a database query.

  2. 02

    Replay the transform

    Run the same filters, joins, aggregates, and calculated columns in the same order.

  3. 03

    Write the result

    Update or add, replace, or append rows in Google Sheets or a database table.

  4. 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 Ads
  • Meta Ads (coming soon)
  • Google Sheets
  • Snowflake
  • BigQuery
  • PostgreSQL
  • Supabase
  • MySQL
  • SQL Server
  • Amazon Redshift
  • Airtable
  • Tableau

Deliver to

  • Google Sheets
  • Snowflake
  • BigQuery
  • PostgreSQL
  • Supabase
  • MySQL
  • SQL Server
  • Amazon Redshift

Every plan can deliver to Google Sheets. Database destinations are available on Pro and up; 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.

One flow, start to finishGoogle Analytics, Search Console and Google Ads, cleaned and joined, then delivered to a Google Sheets tab every week.

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 + Google Ads → 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 + Google Ads → 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.

  1. 01ChatGPTOpen a balanced comparison prompt in ChatGPT.
  2. 02ClaudeOpen the same research prompt in Claude.
  3. 03PerplexityResearch the comparison with linked web sources.

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.