Methodology
Evidence first. AI last.
Fusellit separates truth from interpretation. Raw uploads are preserved, normalized metrics are calculated by deterministic workers, Market Memory connects data to historical outcomes, and AI explains the evidence only after the scoring engine has produced measurable signals.
| Layer | Purpose |
|---|---|
| Raw Data | Original uploads and source evidence are preserved without silent rewriting. |
| Normalization | Workers extract revenue, SEO, product, database, code and operational metrics. |
| Market Memory | Metrics are linked to comparable assets, sale events, failures, recoveries and analyst notes. |
| Scoring Engine | Risk scores are calculated from rules, coefficients and historical patterns. |
| AI Explanation | AI generates readable summaries, risk narratives and decision context without inventing source numbers. |