What we built, and what it changed.

High-volume recruitment teams spend most of their week on administration rather than hiring. Reading CVs, chasing applicants, arranging interviews and rekeying the same details into three different places.

Speed decides the outcome. An applicant contacted within minutes converts. The same applicant contacted two days later has usually accepted something else, so every hour of delay is money spent on advertising that produces nothing.

And because the process lived across inboxes, spreadsheets and messaging apps, there was no reliable record of what had happened. Reporting was assembled by hand, late, and disagreed with itself.

Graduates and international students apply into the hardest market on record, and most cannot tell which employers are even able to sponsor them. The information exists, but only as a raw public register nobody can use.

The advice they receive is generic. A CV is either accepted or ignored, with no explanation, so nothing improves between applications.

Careers teams have the same problem multiplied by a cohort. Hundreds of people, no visibility of who is progressing, and no way to intervene before it is too late.

AI features spend money on every single request, and almost no organisation can say what one customer costs them in a month. The invoice arrives, and the reason for its size is no longer recoverable.

The controls meant to prevent that are usually written once, reviewed once, and never seen to work. A limit that has never been watched stopping something is an assumption, not a control.

The result is a budget nobody can forecast and a risk nobody can quantify, attached to the part of the product the business is betting on.