Provenance
Data & sources.
Every figure in this report is computed directly from the synthetic demonstration corpus below — a fictional firm's book, generated to exercise every lens with a known, verifiable ground truth.
What was analysed
| Corpus element | Count |
|---|---|
| Matters | 30,000 |
| Instructions | 8,000 |
| Parties | 60,046 |
| Connections | 150,666 |
| Keydates | 110,587 |
The synthetic demonstration corpus, by element.
How it was computed
Method
- Configuration & lifecycle — form-field fill rates, phase ages, and standards alignment computed via pandas over the corpus CSVs (the productised pipeline:
insights.audit). - Matter taxonomy & universe — all-MiniLM-L6-v2 sentence embeddings, UMAP 3D projection, KMeans clustering, cluster labels from a local LLM (SGLang) — all on-premise.
- Entity resolution, limitation triage, workload, conflict radar — direct queries over the corpus, proven on a live client engagement and being generalised into the productised pipeline.
On real engagements: client data never leaves a controlled environment — analysis runs on-premise, and only aggregates and evidence trails appear in deliverables. This report is entirely synthetic data; no client information is represented anywhere in it.