Deterministic alignment in place of LLM extraction
In production as AltsByClick, formerly DocEdge AI
- Question
- Capital account statements, capital calls, distributions, and valuations arrive as PDFs in whatever layout each administrator prefers. LLMs misread them in ways that are hard to detect. Can they be parsed without trusting an LLM to read them correctly?
- Method
The patent-pending approach profiles every item on the page and uses Shannon entropy to rank which features actually tell one field from another. It identifies the landmarks, the labels that stay put from one statement to the next, then globally aligns each new statement to the last one from the same source, so a value is found by where it sits relative to those landmarks.
The LLM is confined to four narrowly scoped, checkable roles, such as naming a field the first time it appears.
- Result
- Accuracy does not rest on the model. Every match is validated in both directions, and reconciliation checks flag any figure that is inconsistent or unsupported. It is live with a family office, consolidating a multi-custodian portfolio that is mostly alternatives into one view, and it feeds a monitoring tool that computes beta, volatility, drawdown, and related risk analytics.
- Side benefit
- No templates and no manual entry, at about one-hundredth the cost of extracting the same documents with an LLM.