An AI tool that structures messy problems into decisions

Problem

Problem analysis usually starts from messy notes, with facts, opinions and open questions mixed together and no clear recommendation. Messy, unstructured information blocks decisions.

What I did

• •Validated the customer problem in 50+ one-on-one conversations with former colleagues and industry connections, then defined DeciBrief’s strategy and requirements, prioritizing features by customer impact.
• •Built and launched DeciBrief, an AI decision-support tool that turns messy notes into a clear recommendation, options, trade-offs, ranked risks, unknowns and next actions — the structure of a problem statement and corrective-action review.
• •Set the success metric — time to a clear decision — and the cost and risk guardrails: the no-cost demo is separate from live AI use, to control cost per use and operational risk.
• •Owned it end to end through workflow design, release and iteration.

Verified result

Launched and live at decibrief.com, built around one success metric — time to a clear decision — with the free demo kept separate from live AI use.