Spreadsheets are genuinely good tools — the problem is almost never the sheet, it is the person copying numbers into it every morning, or forgetting to on the one day it mattered. We automate the sheet rather than replacing it: pulling data in from your forms, inbox, CRM or an external system on a schedule, writing it into the right tab, and triggering whatever needs to happen next. It gets most businesses the benefits of a database without a migration project.
Spreadsheets are genuinely good tools — the problem is almost never the sheet, it's the person copying numbers into it every morning, or forgetting to on the one day it mattered. That manual step is where the mistakes creep in: a row skipped, a formula overwritten, an out-of-date version emailed around. Automating the sheet itself, rather than replacing it, usually gets a business most of the way to "having a database" without a migration project.
Form or website enquiry → new row added to the right sheet automatically, with its source and timestamp
Scheduled job → pulls data from an API or another system each morning or evening and writes it straight into the sheet
Row added or updated → triggers an email, a Slack message or a CRM update, so the sheet drives everything downstream
Several data sources → merged and reconciled into one sheet overnight, so nobody copies figures between tabs by hand
Sheet reaches a threshold — stock low, budget spent, a date passed → an automatic alert before it becomes a problem
Recurring report → built straight from the sheet's data and emailed out on a schedule, without anyone opening it
Punthub's prediction pipeline puts Google Sheets right at the centre of the data flow: Python pulls in 6 live data sources every evening, runs them through 7 prediction models, reconciles everything across 21 automated jobs, and writes the results straight into the sheet, no one touching it by hand, ready before Supabase and the live site sync overnight.
21
reconciliation jobs run automatically into the sheet, every night
How we count — what this number measures, and what we have not finished checking.
Sheets are fine for most businesses well past the point people assume — you can automate the writing and reading, add validation, and connect it to other tools, and it holds up for a surprisingly long time. The tipping point is usually volume (thousands of rows updating constantly) or several people editing at once and tripping over each other; that's when a proper database like Supabase or Postgres starts paying for itself. We'll tell you honestly which side of that line you're on.
Yes — most of what we build runs on a timer, whether that's every few minutes, once a night, or first thing every morning, so the sheet is current before anyone opens it. Nobody has to remember to run anything.
One automation — data pulled into a sheet on a schedule, or a row written when something happens — is from £500, fixed price. Fixed price, agreed before we start. You own the code, and nothing is charged monthly unless you later ask for the support plan. Starter builds do not need an audit. The audit is for businesses deciding which bigger system to build first. A pipeline drawing on many sources or feeding a dashboard is a custom build from £3,000.
No — we write into the sheet the way a careful person would, respecting the tabs, formulas and formatting you already have rather than overwriting the whole thing. If a formula depends on a cell we're updating, we test it before going live so nothing quietly stops calculating.
Yes — a lot of what we build reconciles several sheets or external sources into one clean view, so you get one place to look rather than six tabs open at once. That's usually the point where it starts to feel like a database, without the disruption of migrating to one.
Pick a slot below and we'll talk through your business — what's worth automating, what isn't, and what it would cost. Prefer email? Use the form.
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