Earlier quoted context omitted.
Of course. Most of the AI cases (that turn out to be an actual success) focus around a few repeatable patterns and a limited use of "AI". Here are a few interesting ones: (1) Data extraction. E.g. extracting specs of electronic components from data-sheets (it was applied to address a USA market with 300M per year size). Or parsing back Purchase Order specs from PDFs in fragmented and under-digitized EU construction m…
That last point (compliance gaps in fintech) sounds fascinating. Is there a place that I could read more about this?
0. (the most painful step) Carefully parse all relevant documents into a structural representation that could be walked like a graph.
1. Extract relevant regulatory requirements using ontology-based classification and hybrid searches.
2. Break regulatory requirements into actionable analytical steps (turning a requirement into checklist/mini-pipeline)
3. Dynamically fetch and filter relevant company documents for each analytical step.
4. Analyze documents to generate intermediate compliance conclusions.
5. Iteratively validate and adjust analysis approach as needed.
6. Summarize findings clearly, embedding key references and preserving detailed reasoning separately.
7. Perform gap analysis, prioritizing compliance issues by urgency.