From default vendors to a fit-for-purpose stack.
Anonymized client. Account attested by Average Robot.
The client is not named and the account reports no figures. It is Average Robot's own record of the engagement.
The tension
This client already believed in AI and wanted to move faster. For a believer, the risk is not skepticism, it is speed. The danger is bolting AI onto the obvious vendor and locking in a poor fit that only shows itself months later, once it is expensive to unwind.
The surface story
A design-led furniture brand that wanted to take the repetitive, low-value, time-consuming work out of the business, and to understand AI's role in doing it. They were already sold on AI. They wanted speed.
The default path
Add AI through the nearest existing vendor and find its limits only once they were built into the business.
The ground truth
Working through People, Process, and Platform, there was nothing to convince them of. What they were missing was a clear read on the real options. Left to it, they would have taken the nearest vendor on instinct and only found the ceiling of that decision later, when changing course meant ripping out work they had already paid for.
The reframe
The question was which option fits, the out-of-the-box one or something custom, before the choice hardened into a commitment.
The design
We read what they actually needed, then introduced them to both an out-of-the-box provider and specialist consultancies that could build something custom, so the decision was made on fit, not on whoever was easiest to reach.
The outcome, across People, Process, and Platform.
Process
The approach is built to take the repetitive, low-value work out of the business, with AI handling the parts that drain people's time.
Platform
It widens the field to a better-fitting set of options, the out-of-the-box provider or a custom build, rather than the nearest default and the years of poor fit that follow it.
The value was not convincing them AI matters. It was a trusted read on the options.