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LegalAI implementation case study

Legal – Regional Litigation Firm (120 Attorneys): Discovery & Document Review Automation

End-to-end AI for ingest, privilege review assist, deposition prep packages, and production logging for complex litigation.

This case study documents a real client implementation. Identifying details may be withheld where confidentiality applies.

Key takeaway

Full AI automation across discovery operations replaced ad-hoc contract attorney armies with repeatable, auditable agent workflows.

The engagement

From operational friction to a connected AI system

01 · Context

Business overview

Industry: commercial litigation. Size: 120 attorneys. Complexity: multi-district, sensitive sectors. Systems: Relativity, client data rooms.

02 · Challenge

Core problem

Manual linear review, inconsistent privilege, slow narrative prep. Scale issues on large custodian sets.

03 · Approach

Solution

PrimeAxiom built a review orchestration platform: AI-assisted coding suggestions, privilege models with human override, automated privilege logs, and deposition prep agents pulling synchronized excerpts.

04 · Impact

Results

Review throughput +2.1x; privilege QC incidents −76%; partner prep time −34%; outside review spend −28% on comparable matters.

System design

The full automation system

The implementation connects triggers, AI decisions, business rules, human approvals, and downstream actions in one controlled workflow.

Ingest pipelines, AI coding with confidence bands, privilege separation workflows, production export checks, deposition notebooks auto-built.

Workflow

How the automation runs

1. Trigger: load production set. 2. AI clusters near-duplicates; suggests codes. 3. Structured review decisions in DB. 4. QC rules sample for privilege. 5. Export with logs; exception reports. 6. Partner review on edge cases. 7. Feedback retrains rankers.

Intelligence layer

AI agents and decision logic

Coding Agent, Privilege Agent, Dupe Cluster Agent, Deposition Notebook Agent, Production QC Agent.

Under the hood

Technical architecture

Air-gapped options, enterprise LLM, Relativity SDK, immutable audit trails.

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