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

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

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

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

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.

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

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

Relativity API, Azure Gov options, PostgreSQL, OpenAI enterprise, custom review UI

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

Build: 14 weeks. Deploy: matter-by-matter. Optimization: model refresh per practice group.