for companies

Make the data useful without hiring for it.

You don’t need a data platform, a machine learning engineer, or six months of internal training. You need the report to be right, the dashboard to be trusted, and the export to stop eating three days a month.

01

Four problems this usually comes down to

The numbers live in five places

Stripe, the CRM, a warehouse export and two spreadsheets. Every question means reconciling them by hand first, so most questions don’t get asked.

Nobody trusts the dashboard

It exists. It disagrees with finance. So people export to Excel anyway and the dashboard quietly becomes decoration.

The monthly report costs three days

Someone capable spends a third of a week copying, pasting and formatting. That work is a script, and it should run at 6am on the first.

The AI pilot never shipped

A tool was bought, a workshop happened, and nothing reached production because nobody owned the boring middle: clean inputs, a real evaluation, somewhere to put the output.

02

What we build for you

Scoped as fixed-fee projects. You can start with one and stop there.

Data auditTwo weeks. We map the sources you point us at, set out what conflicts, and give you a written plan with costs. Useful even if you build the rest in-house.
PipelinesScheduled Python jobs that pull from your tools, clean and reconcile, and land tables your team can open without asking anyone.
Dashboards in Google WorkspaceYour numbers land in Sheets and refresh on a schedule through Apps Script. Nobody installs anything, nobody buys a seat, and the people who already live in Sheets can keep working exactly as they do.
Models where they payChurn scoring, demand forecasting, segmentation, lead prioritization. Backtested and compared against your current guess before it goes live.
AI upskilling for your teamHands-on sessions for the people who will actually use this, run on your own data rather than a toy dataset. What these tools do well, where they quietly get it wrong, how to check an answer, and how to write a prompt that holds up. Your team stops waiting for a specialist.
Internal tools & sitesThe form, the portal, the approval queue, the marketing site. Built properly rather than assembled from eleven subscriptions, and deployed to hosting in your own name.
AutomationRecurring reports, reconciliations and exports moved onto a schedule, with alerts when something looks wrong. Often this is a few hundred lines of Apps Script sitting quietly inside the Workspace you already pay for.
03

About the AI part

We use it where it earns its place.

Classification, extraction from documents, summarizing free-text feedback, forecasting. These are real and we build them. But a model on top of inconsistent data produces confident nonsense, so the pipeline comes first, always. If a rules-based script does the job for a tenth of the cost, we’ll tell you and build that instead.

Your team doesn’t have to become experts.

Handover includes a walkthrough session and a README written for whoever inherits it, not for us. The measure of a good project here is that you could fire us and keep running.

04

Engagements

Priced per project after the scope call, so you see the number before anything starts.

AuditFixed fee, two weeks. Source map, conflicts, and a costed build plan. No obligation to continue.
BuildFixed fee, scoped up front. A working link in week one, delivery in weeks, code transferred at the end.
RetainerMonthly, cancel anytime. Changes, new dashboards, and someone on call when a pipeline breaks.
05

Send us the messy version.

Describe the report, the decision, or the spreadsheet that keeps breaking. We’ll come back with what it would take.