Skip to content

Data & Intelligence

Integrated pipeline: every source, checked, every morning

Your numbers come from six or seven systems. An integrated pipeline brings them into one place on a schedule, checks each delivery before anything uses it, and sends the results where they're needed: reports, dashboards, and back into the CRM. When a source fails its check, the outputs built on it say so, and the person who owns that source hears first. We build it on the systems you already run, with a named owner for every source.
Talk through your dataFollow one morning ↓
Morning run · Oct 1CRM✓ 05:40Scheduling✓ 05:42Accounting12 of ~140 rowsAd accounts✓ 05:45Call tracking✓ 05:47Web forms✓ 05:48One placecheckedWeekly reportrevenue held · Sep 30 dataOps dashboardrevenue held · Sep 30 dataCRM syncfreshfinance lead alerted · 05:54

The numbers are only as good as last night's exports

Most businesses already move data around: an export from accounting, a script that copies leads, a spreadsheet someone refreshes on Monday. Each works until it doesn't, and when one fails quietly, the report still goes out, with a hole where the revenue should be.

An integrated pipeline replaces those pieces with one system. Every source arrives on a schedule, is checked against what's expected, and only then feeds the outputs that depend on it. When something is wrong, the right person knows before the numbers are used.

Today, and with an integrated pipeline

Today

  1. 01Exports, scripts and spreadsheet refreshes, each set up by someone different.
  2. 02Nobody checks whether last night's export arrived complete.
  3. 03A failure shows up as a strange number in a meeting.
  4. 04Fixing it means finding who set it up.

The numbers are trusted until the day they're wrong, and nobody can say for how long they've been wrong.

With an integrated pipeline

  1. 01Every source arrives on a schedule, into one place.
  2. 02Each delivery is checked for volume, freshness and format before it's used.
  3. 03A failed source holds only the outputs that depend on it, and they say so.
  4. 04The source's owner is told, with what failed.

The morning's numbers are either right or clearly marked.

One morning, step by step

October 1, from the first extract to the refreshed revenue.

Events

Run · Oct 1

Sources
6 extracts running
Checks
—
Store
—
Report
—
Dashboard
—
CRM sync
—
Alerts
—

Event 1 of 8: extracts.started

The parts it's built from

Each part is built and tested on its own, so you can start with one and add the rest.

  1. Arrive

    Data Ingestion

    Every source on its schedule, with a receipt.

  2. Run

    ETL / ELT Pipelines

    • raw loads
    • rules
    • the schedule

    a check fails → hold what depends on that source; alert its owner

  3. Check

    Data Quality & Validation

    Volume, freshness and format, before use.

  4. Model

    Data Transformation · Data Modeling

    One shape, one set of definitions.

Underneath every stepAPI IntegrationConnects to each system's API or export.

Where people stay in charge

  1. Source owners

    One person per source

    Each source has an owner who hears first when it fails.

  2. Check thresholds

    What “normal” looks like

    Owners set what a normal delivery looks like, and adjust it when the business changes.

  3. Held outputs

    Labelled, not hidden

    Anything held shows the date it's from, so nobody mistakes it for today's.

  4. Run history

    Every morning, recorded

    What arrived, what passed and what was held, for any past day.

What changes from one business to the next

SourcesWhich systems, through which API or export
ScheduleOvernight, hourly, or as changes happen, per source
ChecksVolume, freshness and format rules, and who owns each
DestinationsReports, dashboards, the CRM or other systems that receive the results

A common starting point is Airbyte or custom extractors for the sources, PostgreSQL as the store, dbt for transformations, and n8n or Trigger.dev for scheduling and alerts. These are starting candidates, not requirements.

Is an integrated pipeline the right system?

Good fit

  • Reports or dashboards depend on three or more systems.
  • Exports and scripts break and nobody notices straight away.
  • More systems are coming, and each one adds another export.

Avoid when

  • One system holds everything you report on.
  • The data only needs to move once, for a migration.

How we'd approach it

Most of the early work is listing the sources, agreeing the schedule and the checks, and deciding where results go.

  1. 01

    Understand

    As much as the problem needs

    We map how the work runs today: who does what, which systems hold the records, and where it breaks.

  2. 02

    Design

    Decided before it's built

    Ownership, rules, integrations and exceptions, agreed with you and written down with acceptance criteria.

  3. 03

    Build

    Connected to what you use

    We build the scoped system, connect it to the tools you already run, and test it on the cases that matter.

Related systems

The capabilities underneath

Questions about integrated pipelines

What if a system has no API?

A scheduled export to a folder or an email inbox works. The pipeline picks it up and checks it like any other source.

Where does the data live?

In a database you own, usually PostgreSQL in your cloud account. Nothing is locked in a tool you can't leave.

Who fixes it when a source breaks?

The alert goes to the source's owner with what failed. Pipeline problems, like a changed format, come to whoever runs it, us or your team.

Can it send data back to our systems?

Yes, for example enriched fields into the CRM. Writes back follow the same checks, and each field has one owner.

Get your numbers into one place you can trust

Tell us which systems your numbers come from today. We'll show you how they'd arrive, checked, in one place.

Start a project