( Python automation )

Automate the work nobody should be doing.

Data pipelines, scraping, scheduled jobs and reporting that take repetitive tasks off someone's desk.

Most businesses have at least one job that exists only because software does not talk to software. Someone downloads a report every Monday, reformats it, and emails it on. Someone copies orders from one system into another. Someone checks a supplier site for price changes.

These tasks are small individually and enormous in aggregate. They are also, almost always, automatable in days rather than months.

( What this covers )

Python Scripting & Automation, in practice

Data pipelines

Moving data between systems on a schedule, with the transformations, deduplication and validation that make it trustworthy at the far end.

Web scraping

Collecting public data reliably, handling the sites that change their markup and the ones that would rather you did not.

Scheduled reporting

Reports built and delivered automatically, to an inbox, a spreadsheet or a dashboard, without anyone remembering to run them.

Back office automation

Invoice handling, file processing, bulk updates and the routine tasks that consume mornings.

System synchronisation

Keeping two systems that were never designed to talk to each other in agreement.

Monitoring and alerts

Automation that stays quiet when it works and tells you clearly when it does not, which is the difference between a tool and a liability.

( Worth talking to us if )

Any of this sounds familiar.

Someone on your team does the same task every week
Data is copied between two systems by hand
Reports are assembled manually and are always slightly late
You need data from sources that publish no API
A script already exists, written by someone who has left

( How we work )

The shape of a typical build

01
Watch the task as it is done
We map the real process, including the judgement calls the person makes without thinking about them.
02
Automate the reliable part
Not everything should be automated. We separate what a script can own from what still needs a person, and say which is which.
03
Build to fail loudly
Logging, retries and alerts, so a broken job announces itself instead of quietly producing wrong numbers for a month.
04
Deploy and hand over
Scheduled on infrastructure you control, with documentation written for whoever inherits it.

( What you end up owning )

Everything, and no strings.

The repository, with readable code and comments that explain the why
Deployment and scheduling configuration
Documentation of every input, output and failure mode
Alerting wired to wherever your team actually looks

( Built with )

Python
Pandas
Playwright
FastAPI
PostgreSQL
Celery
Docker

Mainstream tools with deep talent pools, chosen so you are never dependent on us to maintain what we built.

Questions about python automation

How long does a typical automation take?: A single well defined job is often a few days. A pipeline spanning several systems, with validation and alerting, is usually one to two weeks. We quote it fixed once the task is clear.
What happens when a website we scrape changes?: It will, eventually. We build scrapers to fail visibly rather than silently return nothing, so you find out immediately. Repairs are quick because the code is written to be repaired.
Is scraping legal?: It depends entirely on the source, its terms and what the data is. We check before building, and we will tell you if a particular source is a bad idea rather than building it and leaving the question with you.
Can you fix a script we already have?: Usually. We read it first and tell you whether repairing or rewriting is better value, which for a short script is often rewriting.

Tell us what you need building.

Send a brief and you get a written scope, a timeline and a fixed price back within 48 hours. It costs nothing and commits you to nothing.

Get a quote

( Often paired with )

Python Scripting & Automation, in practice

Data pipelines

Moving data between systems on a schedule, with the transformations, deduplication and validation that make it trustworthy at the far end.

Web scraping

Collecting public data reliably, handling the sites that change their markup and the ones that would rather you did not.

Scheduled reporting

Reports built and delivered automatically, to an inbox, a spreadsheet or a dashboard, without anyone remembering to run them.

Back office automation

Invoice handling, file processing, bulk updates and the routine tasks that consume mornings.

System synchronisation

Keeping two systems that were never designed to talk to each other in agreement.

Monitoring and alerts

Automation that stays quiet when it works and tells you clearly when it does not, which is the difference between a tool and a liability.

The shape of a typical build

Watch the task as it is done

We map the real process, including the judgement calls the person makes without thinking about them.

Automate the reliable part

Not everything should be automated. We separate what a script can own from what still needs a person, and say which is which.

Build to fail loudly

Logging, retries and alerts, so a broken job announces itself instead of quietly producing wrong numbers for a month.

Deploy and hand over

Scheduled on infrastructure you control, with documentation written for whoever inherits it.

Questions about python automation

How long does a typical automation take?

A single well defined job is often a few days. A pipeline spanning several systems, with validation and alerting, is usually one to two weeks. We quote it fixed once the task is clear.

What happens when a website we scrape changes?

It will, eventually. We build scrapers to fail visibly rather than silently return nothing, so you find out immediately. Repairs are quick because the code is written to be repaired.

Is scraping legal?

It depends entirely on the source, its terms and what the data is. We check before building, and we will tell you if a particular source is a bad idea rather than building it and leaving the question with you.

Can you fix a script we already have?

Usually. We read it first and tell you whether repairing or rewriting is better value, which for a short script is often rewriting.