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S2

The Post-Mortem

You tried AI, it went nowhere, and nobody can tell you why. This is the written answer.

£1,500
5 days

The problem it solves

Something was built or bought, money and months went in, and the result was quietly shelved. Now nobody will say whether the idea was wrong, the data was wrong, the execution was wrong or the expectation was wrong, so you cannot tell whether to try again.

Who buys it: Anyone whose first AI attempt produced nothing measurable, from a solo operator to a team lead with a shelved pilot.

What lands

  • A written diagnosis naming which layer actually failed: the problem, the data, the execution, or the expectation set at the start.
  • What it would take to make it work, with an honest cost of doing so.
  • A clear recommendation on whether to retry, rescope, buy something off the shelf, or drop it.
  • The specific things to not repeat, so the next attempt does not fail the same way.

What this is not

  • No remediation and no rebuild. This tells you what happened and what it would take.
  • No vendor management and no arguing with whoever built it.
  • Not a code audit of a production system. That is Go / No-Go.

Who shouldn't buy it: Anyone who wants a document blaming a supplier or a colleague. This names causes, not people, and if the cause was the brief you wrote, it will say so.

The guarantee

A named cause or the engagement is free. "It was a mix of things" is not a finding, it is what you already have.

Why me

Roughly 95% of AI projects show no measurable return, so a failed first attempt is the normal outcome rather than a special one. The failure patterns repeat, which is exactly why a week is enough to name yours.

Questions people actually ask

It was a while ago. Does that matter?

Not much. The decisions that caused it are still visible in what was built, what was measured and what was promised at the start. Those are the three places the answer usually lives.

What if it turns out the idea was fine?

That is a common finding and a useful one. Plenty of sound ideas die from a data problem nobody looked at or a success metric nobody agreed. Knowing that changes what you do next.