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Course Outline
LangGraph Fundamentals for Legal
- Refresher on LangGraph architecture and stateful execution.
- Key legal use cases: contract analysis, regulatory compliance, e-discovery.
- Constraints and requirements for regulated legal environments.
Legal Data Standards and Ontologies
- Introduction to legal ontologies and metadata (e.g., common taxonomies).
- Mapping legal documents and clauses into graph state.
- Data quality, PII handling, and provenance.
Workflow Design for Legal Processes
- Designing contract lifecycle and review workflows.
- Decision branching, approvals, and escalation paths.
- Persistence strategies for legal evidence and audit trails.
Compliance, Governance, and Risk Controls
- Policy enforcement and record-keeping requirements.
- Access control, encryption, and secure logging.
- Model risk management and change control.
Human-in-the-Loop and Explainability
- Designing effective review and override points.
- Explainability patterns for legal decisions.
- Generating audit-friendly explanations and summaries.
Integration and Deployment
- Connecting LangGraph to DMS, EDR, and core legal systems.
- Containerization, secrets management, and environment hardening.
- CI/CD for graph deployments and staged rollouts.
Monitoring, Testing, and Safety
- Observability: logs, metrics, traces, and SLOs.
- Test harnesses, scenario testing, and red teaming for legal prompts.
- Drift detection, dataset curation, and continuous improvement.
Summary and Next Steps
Requirements
- Understanding of Python and LLM application development.
- Experience with APIs, containers, or cloud services.
- Basic familiarity with legal domain concepts and document types.
Audience
- Domain technologists.
- Solution architects.
- Consultants building LLM agents in regulated industries.
35 Hours
