Defensible, auditable pipelines for legal eDiscovery — engineered for scale. Build, debug, and harden the systems that move electronically stored information from custodial intake to court-ready production.
Modern eDiscovery operations cannot tolerate ad hoc scripting. The delta between a defensible production and a sanctionable failure is dictated by architecture: immutable state management, cryptographic chain-of-custody validation, and deterministic processing boundaries. This site collects production-focused patterns for ESI ingestion, deduplication hashing, privilege review routing, load file generation, production validation, batch processing, and audit trail generation.
Every guide pairs the architectural rationale with concrete, production-ready Python — structured logging, streaming cryptographic verification, memory-bounded async processing, and explicit failure routing. Diagnostics walk through real failure signatures (OOM kills, hash divergence, schema drift) and the defensible recovery procedures that keep a matter court-ready.
It is written for eDiscovery specialists, litigation support teams, legal tech developers, and Python automation engineers — anyone who has to make discovery pipelines scale without compromising evidentiary integrity.
Defensible pipeline design: ESI format mapping, privilege schema design, security boundaries, and production compliance frameworks.
Architecture for defensible scale: native file ingestion, cryptographic hash generation, PDF/text extraction, and async batch processing.
Production architecture for hash-based deduplication, email threading, attachment parent-child mapping, and similarity thresholds.
