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Course Outline
LangGraph Fundamentals for Government Legal Professionals
- Overview of LangGraph architecture and stateful execution
- Key legal use cases: contract analysis, regulatory compliance, and e-discovery for government
- Constraints and requirements for regulated legal environments in the public sector
Legal Data Standards and Ontologies for Government
- Introduction to legal ontologies and metadata, including common taxonomies for government use
- Mapping legal documents and clauses into graph state for enhanced data management
- Data quality assurance, handling of personally identifiable information (PII), and provenance tracking
Workflow Design for Legal Processes in Government
- Designing contract lifecycle and review workflows tailored for government operations
- Implementing decision branching, approvals, and escalation paths to ensure efficient processes
- Strategies for persisting legal evidence and maintaining audit trails for compliance
Compliance, Governance, and Risk Controls for Government
- Policy enforcement and record-keeping requirements in government legal processes
- Access control measures, data encryption, and secure logging practices
- Model risk management and change control procedures to ensure regulatory compliance
Human-in-the-Loop and Explainability for Government Legal Decisions
- Designing effective review and override points in legal workflows
- Patterns for ensuring explainability of legal decisions to stakeholders
- Generating audit-friendly explanations and summaries for transparency
Integration and Deployment for Government Legal Systems
- Connecting LangGraph to document management systems (DMS), electronic discovery reference (EDR) models, and core legal systems used in government
- Containerization techniques, secrets management, and environment hardening for secure deployment
- Continuous integration/continuous delivery (CI/CD) practices for graph deployments and staged rollouts in the public sector
Monitoring, Testing, and Safety for Government Legal Applications
- Observability practices: logs, metrics, traces, and service level objectives (SLOs) for government systems
- Test harnesses, scenario testing, and red teaming for legal prompts to ensure reliability
- Drift detection, dataset curation, and continuous improvement strategies for maintaining system integrity
Summary and Next Steps for Government Legal Teams
Requirements
- A solid understanding of Python and the development of Large Language Model (LLM) applications for government
- Practical experience with APIs, containers, or cloud services
- Basic knowledge of legal domain concepts and document types
Audience
- Domain technologists for government
- Solution architects for government
- Consultants building LLM agents in regulated industries for government
35 Hours