Learning Focus

  • Understand the evolution from automation to agentic intelligence across real operations.
  • Design AI collaborators that perform planning, execution, evaluation within functional workflows.
  • Build and deploy prototypes using n8n (orchestration) and OpenAI Agent Builder (reasoning).
  • Apply the Model Context Protocol (MCP) to enable multi-agent coordination and contextual memory.
  • Implement self-hosted automation under corporate data-governance policies.
  • Quantify ROI via KPIs like cycle time, turnaround time, accuracy, cost per transaction, SLA adherence, CSAT/NPS ( plus OEE/MTBF where relevant ).
  • Embed AI governance, PDPA compliance, and risk-management practices into deployment cycles.

Participants Will Leave With

  • A functioning on-premise agentic AI prototype for a real cross-department workflow.
  • A tested self-hosted n8n instance configured for secure automation and auditability.
  • A governance framework aligned with Singapore’s Model AI Governance 2.0 .
  • A 90-day roadmap to scale agentic collaboration across functions.
  • Confidence to collaborate with business users (Zapier prototypes) and IT teams (production-grade n8n systems).

Programme Objectives

  • Explain how agentic systems enhance decision-making and operational efficiency.
  • Identify opportunities for human–AI co-work within existing processes.
  • Apply workflow mapping and role decomposition ( Planner → Executor → Evaluator ).
  • Develop and deploy multi-agent prototypes using n8n and OpenAI APIs .
  • Configure secure, self-hosted environments for PDPA-compliant operations.
  • Evaluate performance and ROI via quantifiable KPIs.
  • Establish governance for versioning, retraining, and ethical AI lifecycle management.

Programme Outline

Day 1 – Foundations & System Design

  • From Automation to Agency: Beyond rules—reasoning, planning, feedback loops.
  • Human–AI Collaboration Model: 3A + 2A (Automate, Augment, Accelerate + Agency, Autonomy).
  • Tools Landscape 2026: OpenAI Agent Builder, Claude CrewAI, Flowise/LangGraph, n8n.
  • Agent System Blueprint: Map real workflows (Finance, HR, CX, Ops, Education, Healthcare, etc.) and decompose roles.
  • Context Engineering & Governance: Prompts → structured context (RAG + MCP), PDPA requirements.

Day 2 – Hands-On Agentic Prototyping (n8n Lab)

  • n8n Orchestration: Triggers, nodes, credentials, logic flow.
  • Connecting Systems: Integrate ERP/CRM/EMR/LMS/ticketing via REST/GraphQL; embed OpenAI APIs.
  • Multi-Agent Logic: Implement Planner–Executor–Evaluator patterns with branching and error handling.
  • Self-Hosting & Security: Deploy n8n on Docker; HTTPS, key management, audit logging.
  • PDPA Practices: Environment variables for secrets, log retention, data minimisation/masking.

Day 3 – Integration, Scaling & Compliance

  • Secure Integration & Access Control: RBAC, SSO, credential vaults, least-privilege scopes.
  • MCP Interoperability: Connect n8n workflows with MCP-enabled agents and approved tools.
  • Measuring ROI & Reliability: KPI baselining—time, accuracy, cost, CSAT/NPS (plus OEE/MTBF where relevant).
  • Governance & Lifecycle: Versioning, retraining cycles, incident playbooks; ISO 27001 readiness.
  • Showcase & Next Steps: Final prototype presentations and 90-day implementation roadmap.

Tools Introduced

Category Tool / Platform Purpose
Agentic Builder OpenAI Agent Builder, Google Opal Define intelligent agents using MCP-aware interfaces and policies
Orchestration Engine n8n (self-hosted) Core workflow and logic orchestration
Visual Design Flowise / LangGraph Visualise agent networks and toolchains
API Integration Postman, REST/GraphQL connectors Integrate ERP/CRM/EMR/LMS/ticketing systems
AI Services OpenAI API, Claude Workflows, Vertex AI Search Reasoning, summarisation & document intelligence
Security & Deployment Docker, NGINX, Let’s Encrypt, Linux ACL Self-hosting, TLS, data-residency control
Compliance Toolkit PDPA guidelines, ISO 27001 templates, AI Verify framework Align automation with Singapore AI governance

Self-Hosting & Data Security Practices (Day 2–3 Labs)

  • Deploy n8n in Docker Compose with persistent volumes and encrypted secrets.
  • Configure HTTPS via NGINX + Let’s Encrypt; enforce HSTS and modern ciphers.
  • Apply RBAC and SSO (OIDC/SAML) for internal authentication.
  • Use environment variables for API keys—never store plaintext credentials.
  • Implement structured logging and audit trails to meet PDPA accountability.
  • Create segregated Dev / UAT / Prod environments with change control.
  • Optional: integrate on-prem PostgreSQL for durable state and telemetry.

Expected Outcomes

  • Deployment of a working agentic assistant prototype on self-hosted infrastructure.
  • Governance-ready automation blueprints for your real workflows.
  • A repeatable method to scale trusted, explainable, and compliant AI collaboration across teams.

Bring This Lab to Your Organisation

We run private cohorts on-site. Sessions are tailored to your systems, controls, and goals—supported by pre-lab scoping and data-readiness checks to ensure momentum from Day 1.