Evidence Intelligence for Legal AI
An architecture for trustworthy first-pass case analysis from raw evidentiary records.
CaseGenie is the first step before any downstream legal AI tool. Review the evidence here first. Then carry the lawyer-reviewed report into Harvey, CoCounsel, Claude, ChatGPT, or the tools you already use next.
CaseGenie is a secure evidence vault and first-pass analytical system built on touchless ingestion, whole-record reasoning, and source-tethered output inside a bounded perimeter.
What CaseGenie is
CaseGenie is a secure evidence-intelligence system for litigation. It keeps the full record of a matter in a tenant-isolated vault, reads that record as a coherent whole, and produces a first-pass analytical report grounded in the documents themselves. The analysis is source-tethered and generated without prompt contamination. It is organized for lawyer review, judgment, and acceptance before it is carried into downstream drafting, research, and workflow tools as the clean starting record.
What it produces
A structured analytical record of the matter: the chronology established by the documents, the entities and relationships the record names, the contradictions and gaps the record reveals, the legal theories the evidence may support, and the source-tethered evidence behind each claim. The record is built inside the vault, organized for lawyer review, and exportable as a complete report. Downstream drafting, research, and advocacy happen outside the system — on top of the CaseGenie report, not in place of it.
Who it was built for
Experienced attorneys and the teams deciding how AI should fit into serious legal work. Solo and small-firm lawyers who want an independent first read of a matter before they draft. Plaintiffs assessing whether they have a case. CaseGenie does not replace lawyer judgment. It provides the evidentiary substrate that judgment operates on.
The argument
Legal AI fails when user framing reaches the analytical layer before the system has read the evidence. Two losses follow.
The first is the loss of first-read independence. Once user framing reaches the analytical layer, the system can no longer claim its understanding was independently derived from the record. These papers name that loss prompt stain.
The second is the loss of integration. When the record exceeds what a system can hold at once, something has to do the joining. If prompts, retrieval rules, or retained instructions supply the join, the system is no longer reasoning from the record alone.
The architecture described here is the conjunctive response. Documents are ingested without user framing reaching the analytical layer. The record is read as a coherent whole rather than reconnected by prompts. Every analytical claim is tethered to source. The intelligence service operates inside a bounded perimeter with no outbound integrations — the same architectural property that protects integrity also protects confidentiality.
The full argument is developed in the working papers, working notes, and five-essay foundation sequence collected at /research. The named mechanisms are summarized at /patent. The working product built to the same architecture is in operation at CaseGenie.ai.
Where to start
Legal-AI scholars, ethics readers, and bar-association audiences: start with the working papers and working notes at /research.
Legal-tech press and industry readers: start with the public essay arc at beforeadvocacy.substack.com.
Corporate-development, licensing, and strategic readers: start with /patent and /press.
The architectural claims advanced here can also be inspected directly in four read-only working sample cases.