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Course Outline
LangGraph Fundamentals for Legal Operations
- Overview of LangGraph architecture and stateful execution principles
- Key legal use cases: contract analysis, regulatory compliance, and e-discovery
- Specific constraints and requirements for regulated legal environments
Legal Data Standards and Ontologies for Government Use
- Introduction to legal ontologies and metadata (e.g., common taxonomies)
- Techniques for mapping legal documents and clauses into graph state
- Strategies for ensuring data quality, handling personally identifiable information (PII), and maintaining provenance
Workflow Design for Legal Processes in Government
- Best practices for designing contract lifecycle and review workflows
- Decision branching, approval processes, and escalation paths
- Persistence strategies for maintaining legal evidence and audit trails
Compliance, Governance, and Risk Controls for Government Legal Operations
- Policy enforcement and record-keeping requirements in government settings
- Access control measures, encryption protocols, and secure logging practices
- Model risk management techniques and change control procedures
Human-in-the-Loop and Explainability for Government Legal Decisions
- Designing effective review and override points in legal workflows
- Patterns for enhancing explainability of legal decisions
- Methods for generating audit-friendly explanations and summaries
Integration and Deployment Strategies for Government Legal Systems
- Connecting LangGraph to document management systems (DMS), electronic discovery reference (EDR) models, and core legal systems
- Containerization techniques, secrets management, and environment hardening practices
- Continuous integration/continuous deployment (CI/CD) strategies for graph deployments and staged rollouts
Monitoring, Testing, and Safety Measures for Government Legal Applications
- Observability practices: logs, metrics, traces, and service level objectives (SLOs)
- Test harnesses, scenario testing, and red teaming for legal prompts
- Drift detection methods, dataset curation techniques, and continuous improvement processes
Summary and Next Steps for Government Implementation
Requirements
- An understanding of Python and the development of large language model (LLM) applications for government.
- 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 for government
35 Hours
