A simulation of a global gap assessment with AI prioritization. In the real work, areas and affiliates add input to a register of evidence gaps and an AI gap assessment capability helps validate and prioritize each gap on a multi-dimensional framework. People make every decision.
- Invented data. Every gap, statement, input, score, vote and decision is sample content made up for this demo. Areas A, B and C are sample therapeutic areas; four regions, standing in for the areas that review gaps, and Affiliates 1 to 8 add input and vote.
- Nothing is connected. The AI assistant is scripted and deterministic: the same gap and weights always give the same suggestion. It runs on timers in your browser, no model is called and the demo makes no network requests.
- A simplified framework. Six weighted dimensions, an impact and feasibility matrix and four tiers, chosen for the demo. It shows how such a framework works, not a production scoring rule.
- Stored locally. Your scores, decisions, merges, votes and weights stay in this browser (keys that start with ccdemo-gap-) until you reset the demo in Settings.
New here? The guided path prioritizes one sample gap in under a minute.