Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 35 hours
Course Outline
LangGraph Fundamentals for Finance
- Review of LangGraph architecture and stateful execution.
- Finance use cases: research copilots, trade support, and customer service agents.
- Considerations for regulatory constraints and auditability.
Financial Data Standards and Ontologies
- Foundations of ISO 20022, FpML, and FIX.
- Mapping schemas and ontologies to graph state.
- Managing data quality, lineage, and PII.
Workflow Orchestration for Financial Processes
- KYC and AML onboarding workflows.
- Trade lifecycle, exception handling, and case management.
- Credit adjudication and decisioning paths.
Compliance, Risk, and Controls
- Policy enforcement and model risk management.
- Guardrails, approval workflows, and human-in-the-loop steps.
- Establishing audit trails, retention policies, and explainability.
Integration and Deployment
- Connecting to core systems, data lakes, and APIs.
- Containerization, secrets management, and environment configuration.
- CI/CD pipelines, staged rollouts, and canary releases.
Observability and Performance
- Structured logging, metrics, tracing, and cost monitoring.
- Load testing, SLOs, and error budget management.
- Incident response, rollback procedures, and resilience patterns.
Quality, Evaluation, and Safety
- Unit, scenario, and automated evaluation harnesses.
- Red teaming, adversarial prompting, and safety checks.
- Dataset curation, drift monitoring, and continuous improvement.
Summary and Next Steps
Requirements
- Proficiency in Python and LLM application development
- Experience working with APIs, containers, or cloud services
- Familiarity with financial domains or data models
Audience
- Domain technologists
- Solution architects
- Consultants developing LLM agents within regulated industries
