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

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