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Memory for legal AI.
Keep matter memory current while preserving source versions, privilege boundaries, policy, tools, and review.
$ mem.recall_at(matter="m-4471", query="liability cap", as_of="2025-03-01") # → "$2M" (the cap in force then, before the amendment) $ path(from="attorney:jdoe", to="party:acme") # → conflict (reachable via a former-client edge)
Proof points
Walls, cutoffs, custody.
Matter walls enforced at the database layer via row-level security, not application checks a bug can bypass.
recall_at for privilege cutoff and production-date reconstruction.
Tamper-evident audit trail for every access and change.
Reachability from attorney to adverse party through the relationship graph.
Crypto-shred keyed by matter or client, with custody-preserving erasure.
Matter, jurisdiction, claim type, party, privilege date, and document-type normalization.
See it: as-of recall
Recall access by date.
A first production boundary
Start with one matter workflow that carries real review risk.
Map the source documents, matter and privilege scope, model output, policy checks, reviewer, and downstream work product. Then test whether the original evidence boundary survives amendments, new productions, team changes, and later investigation.
Connector priorities
Where the documents live.
iManage, NetDocuments, Relativity, Clio, SharePoint, Box, Microsoft Purview, and eDiscovery exports.