Legal AI Operating System

5 layers · 8 functions · 4-dimension Harvey monitoring · 89 indexed help docs · 52 tests

~2,500

Attorney Hours Saved / Year

~$600K

Client Value Delivered / Year

100%

Decisions Auditable & Traceable

Tests · 21 Harvey Monitor · 31 ROI

L0: Knowledge Foundation L1: Governance & Trust L2: Legal AI Functions L3: Program Operations L4: Organizational Model

Input

document · query · matter

→

Router

classify · jurisdiction

→

Evaluator

LLM reasoning · structured output

→

Scoring

programmatic · never trusts LLM

→

Audit Trail

append-only · full lineage

Layer 0

Knowledge Foundation

Client documents, precedents, playbooks, and regulatory sources — RLS-enforced walls between clients, vector-indexed for semantic search.

Client Documents

Contracts, policies, correspondence, pleadings. RLS-enforced isolation ensures no cross-client leakage.

Precedents & Playbooks

Negotiation history, position papers, escalation rules. Vector-indexed for semantic retrieval.

Regulatory Sources

15-20 agencies monitored. Changes extracted, classified, matched to active matters within 24 hours.

data flows up · governance flows down

Layer 1

Governance & Trust

The layer Harvey doesn't provide. Every decision auditable, explainable, and traceable — by architecture, not by policy.

Audit Trail

Every LLM call recorded: full prompt, response, model, tokens, cost, processing time. Append-only. Immutable.

Explainability

LLM provides reasoning. System provides judgment. Never the reverse. Scores are programmatic, not self-assessed.

Traceability

Full lineage: input → router → evaluator → scoring → human review → disposition. Every step recorded.

Confidentiality (RLS)

Row-Level Security enforces client data isolation at the database layer. Technical walls, not policy promises.

Human-in-the-Loop

Configurable thresholds for mandatory review. Auto-escalation on low confidence. Risk-tiered gating.

Compliance Readiness

ABA Formal Opinion 512 (6 duties). SOC 2 evidence framework. ISO 42001 alignment. Audit-ready, not self-certified.

governance wraps every function invocation

Layer 2

Legal AI Functions — 8 POC Demos + Maturity Assessment

Each function follows the same governed pipeline. Harvey handles production equivalents — these are auditable reference implementations demonstrating the governance architecture.

Matter Intake & Triage

94% accuracy · 180× faster

Contract Review

800+ contracts/year · 160× faster

Employment Agents

US/EMEA/AU · RLS walls · filings

Cowork Legal Plugin

9 skills in Claude · 100% adoption

Due Diligence

87% time reduction · deviation-only

Regulatory Monitor

<24hr detection window · 15-20 sources

KM & Precedent

Semantic search · ~120 hrs saved/year

Value Reporting

Quarterly reports · 100% audit-backed

AI Maturity Assessment

Org readiness · gap analysis

measurement layer · what Harvey can't measure itself

Layer 3

Program Operations

The K&I Program Manager's daily toolkit. Everything needed to measure, govern, and enable — built and deployed.

Portfolio Dashboard

KPI cards (hours saved, cost avoided, net ROI, adoption). Function breakdown table with tooltips. Quality metrics section. Hours-saved bar chart. Period selector (30/90/365 days).

$62K

multi-step AI cost

67%

adoption rate

ROI Framework

Cost impact = time saved × billable rate from rate cards. Quality metrics: accuracy, override, false positive rates. Adoption = active / eligible users. Calibrated baselines with methodology.

5:1

ROI ratio

91%

accuracy rate

POC Pipeline

Kanban board: Discovery → Build → Review → Graduated / Cancelled. Project cards with feedback log. Auto-timestamped status transitions. Client and practice group assignment.

Harvey Agent Monitoring

4-dimension independent evaluation of Harvey outputs: Accuracy, Safety, Bias, Compliance. Weighted scoring (Tier 1 at 1.5×). Hard veto at 75. Drift detection (6 types). Certification: Platinum→Bronze. Agent registry + evaluation history.

90.5

avg final score

5.3s

4-dim eval time

Enablement Kit

Workshop deck outline (60 min). Prompt engineering guide. Adoption playbook. AI literacy FAQ. Client conversation deck. RFP response templates. Technical FAQ for client CISOs.

Agentic Help System

RAG-powered chat: Voyage AI embeddings → vector search → LLM answer with source references. 11 indexed docs, 89 chunks. Slide-out panel with suggested questions. Local FAQ fallback when API unreachable. Thumbs feedback.

role definition · interface maps · success metrics

Layer 4

Organizational Model

The K&I Program Manager role — what it owns, what it doesn't, and how it interfaces with every team.

K&I Program Manager

Reports into Technology. Sits on K&I. Bridges practice groups, Harvey, and client teams. Makes AI measurable, auditable, and teachable.

Technology

Owns Harvey deployment and infrastructure. K&I PM provides requirements and evaluation criteria — does not own the vendor relationship.

L&D

Partners on AI literacy. K&I PM provides enablement materials, workshops, and adoption playbooks. Joint delivery on upskilling.

Pricing / LPM

Owns AFA and pricing strategy. K&I PM provides cost-impact data (time saved × rates) — the evidence, not the pricing decisions.

Client Teams

K&I PM serves as strategic advisor on AI as value-added differentiator. Provides client conversation materials and governance evidence.

12-Month Success Metrics

Framework deployed. Pipeline active. Adoption tracked. Client reports delivered. AI literacy baseline established. Governance evidence ready for client audit.

One platform. Five layers. Knowledge → Governance → Functions → Operations → Organization. The LLM provides reasoning. The system provides judgment. Every number in the dashboard is backed by an append-only audit trail. Every Harvey output can be independently scored. Every lawyer has the training and tools to use AI confidently. This is what it looks like when AI is measurable, auditable, and teachable.