Interactive Case Study · Active Lab

eDiscovery Processing Platform

A POC platform scoped to EDRM Processing and Production — multi-format document intake, automated enrichment and triage, matter-scoped review, an AI matter assistant, and a defensible chain of custody. Built to validate the core workflows used by litigation support teams before documents reach review.

Intake

Multi-format ingestion with deduplication

Enrichment

Automated entity extraction and relevance scoring

Review

Matter-scoped triage workspace and smart folders

Defensibility

Immutable custody log and full audit trail

Processing Flow

End-to-end flow from source documents through extraction, enrichment, and operator review surfaces.

Source DocumentsLoose files and load filesReceived ProductionsStandard load-file formatsExtraction PipelineText, metadata, dedup, indexDocument StoreFiles, full-text, metadataEnrichment EngineEntities, relevance, flagsReview ConsoleFolders, decisions, searchAI Matter AssistantChat and background analysisCustody and AuditImmutable event chain

Shipped Capabilities

  • Multi-format document intake with automatic deduplication and job-level status tracking
  • Standard load-file support — Concordance, Opticon, and IPRO formats — preserving Bates ranges, family groupings, and custodian attribution
  • Full-text extraction and search indexing across all ingested document types
  • Automated entity recognition, relevance scoring, and privilege flag detection — surfaces likely key documents without manual triage
  • Three-panel review workspace with smart folders, decision tracking, annotations, and matter-scoped search
  • AI matter assistant scoped to each matter — generates summaries, tag suggestions, entity analysis, and workflow recommendations
  • Immutable custody log with hash-chained events and full audit trail for legally defensible processing records

Scope and Design

The platform targets EDRM Processing and Production only — not collection, full review lifecycle management, or presentation. This keeps the build focused on ingest fidelity, operator triage, and production readiness rather than end-to-end litigation platform breadth.

Validated with real data

End-to-end pipelines verified using the Enron email corpus and EDRM format test data — 879 documents ingested, 5 custodians, 588 documents enriched across 3 active matters.

AI Matter Assistant

Each matter gets a scoped assistant with full awareness of its document population — counts, top entities, privilege flags, and recent excerpts. Operators can chat or trigger background analysis jobs without leaving the review console.

Background analysis jobs

Matter summaries, tag suggestions, entity analysis, workflow recommendations, and QA context — triggered on demand or on schedule.

Model-agnostic design

Local or hosted models swap without application code changes — the assistant behavior stays consistent regardless of underlying provider.

Roadmap

The following areas are planned or in progress — not yet complete in the POC.

Bates export and production packaging

Numbered export sets with configurable prefix and start range — production-set UI exists; generation is in progress.

Custom field mapping profiles

Configurable column maps for non-standard load-file ingestion, with auto-detection and a management UI.

Enterprise access controls

Role-based permissions per matter — not in scope for the initial POC; targeted for the next phase.

Structured AI actions

Direct lookups and workflow triggers from the assistant — moving beyond context-aware chat to discrete, auditable actions.

Native document viewer

In-console rendering of original files alongside extracted text — currently shows extracted text only.

External integrations API

Standalone API layer for connecting external review platforms and downstream litigation tools.

Background

This lab builds on five years of eDiscovery platform work at Cicayda (2017–2021), where I led development of a social media eDiscovery system for multidistrict litigation, modernized cloud infrastructure, and coordinated engineering through acquisition. The POC here is an independent DH7 Systems build — focused on processing fidelity, operator UX, and defensibility — not a continuation of employer product code.

Demo Environment

The eDiscovery console runs against the Enron email corpus and EDRM format test data, showing matter management, processing job status, and enrichment results. The demo environment is currently offline — a live walkthrough is available on request.

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