Explore my work — live demo
Guided demonstrations
Demo 1
ServiceNow IRM & Enterprise Governance Lab
Problem: Control failures are tracked in email and spreadsheets, so findings lack consistent scoring, ownership, due dates and approval evidence.
Experience: Relates to my GRC work involving NIST 800-53 control assessments, audit finding tracking, POA&M and ServiceNow IRM.
Approach: Configurable risk scoring, a control → finding → remediation → approval workflow on the automation engine, and an executive dashboard computed from records.
- 1. Workspace → Record control test: pick AC-2, review the evidence, choose Fail (optionally tick cross-lab propagation)
- 2. Automation tab → approve the pending remediation plan
- 3. Workspace → Remediation table → Complete remediation with closure evidence
- 4. Dashboard → confirm the control is Effective again; Reports → download the PDF
Demo 2
ServiceNow Administrator & Developer Lab
Problem: Platform changes made without RBAC, validation and change control introduce risk and rework.
Experience: Relates to ServiceNow IRM configuration and workflow concepts used in my GRC roles.
Approach: An independently built ServiceNow-style simulator: tables, data policies, declarative business rules, ACL evaluation, flows on the automation engine, a Table API, update sets and rollback.
- 1. Demo 1: Create table (default fields provided), then Insert record
- 2. Demo 2: Create flow on the table with approval; insert a matching record → approve in Automation
- 3. Demo 3: ACL check as ro.viewer create → DENY; as ana.analyst → ALLOW
- 4. Demo 4: Create business rule; insert a record and see rules fired
- 5. Demo 5: REST call GET/POST and inspect status & latency
- 6. Demo 6: Create change → approve CAB → Test pass → Deploy → Rollback
Demo 3
Cybersecurity Risk & Controls Lab
Problem: High-severity vulnerabilities and weak controls are not consistently translated into risk records with owners and SLAs.
Experience: Relates to my vulnerability management, risk assessment and NIST CSF/800-53 mapping work.
Approach: Likelihood × impact inherent risk, control-effectiveness residual risk, heat map, and automation for CVSS ≥ 7 or residual ≥ 12.
- 1. Add a vulnerability with CVSS 8.1+ on a critical asset → automation creates risk + remediation
- 2. Assess a risk with low control effectiveness to trigger the residual-risk rule
- 3. Treat a risk with Accept → approval workflow
- 4. Review the heat map in Dashboard
Demo 4
IT Audit, SOX & Regulatory Compliance Lab
Problem: Evidence requests, test results and findings are disconnected, making readiness hard to measure.
Experience: Relates to my SOX ITGC, audit management and audit-finding tracking experience.
Approach: Engagement planning auto-generates control tests and evidence requests; failed tests create findings and management action plans; remediation is verified.
- 1. Plan an engagement (choose a framework) → tests & evidence requests are generated
- 2. Submit and review evidence
- 3. Record a failed test with exceptions → finding + action plan
- 4. Verify remediation; watch readiness score
Demo 5
Third-Party Risk Management Lab
Problem: Vendors are onboarded without risk-based tiering, so critical vendors get the same light review as low-risk ones.
Experience: Relates to my third-party risk management and vendor assessment experience.
Approach: Onboarding triggers classification, tiered questionnaire, SOC 2 review, residual scoring, reviewer assignment, approval and inventory update (Workflow 2).
- 1. Onboard a vendor with regulated data + network integration
- 2. Approve it in Automation
- 3. Answer the questionnaire (some No answers create remediation)
- 4. Raise a continuous-monitoring event
Demo 6
AI Governance, Model Risk & Responsible AI Lab
Problem: AI adoption without inventory, risk tiering and oversight creates privacy, fairness, security and accountability gaps.
Experience: Relates to my AI governance focus and independent AI product development (AI agents, model evaluation).
Approach: Registration triggers risk tiering, required assessments with checklists, reviewer assignment, an AI Agent Manager review, board approval and monitoring (Workflow 3).
- 1. Register a high-impact AI system
- 2. Inspect the generated assessments and the agent recommendation
- 3. Approve in Automation → monitoring enabled
- 4. Complete checklist items; record an evaluation; report an AI incident
Demo 7
AI Agent Manager & Agent Operations Command Center
Problem: Agents without least privilege, approval gates, evaluation and cost visibility create operational, security and budget risk.
Experience: Relates to my independent AI product development (D3 Command): AI agents, model evaluation, latency and token cost.
Approach: Agent registry with versioning and allowlisted tools; multi-agent workflows on the automation engine; guardrails; evaluation datasets; cost/latency analytics from recorded runs.
- 1. Demo A: Create an agent, then Test it
- 2. Demo B: Run multi-agent GRC assessment → approve the Human reviewer gate → open the report
- 3. Demo C: Security test with tool send_external_email → blocked + incident
- 4. Demo D: Evaluate an agent on the 8-case dataset
- 5. Demo E: Compare model configurations
- 6. Demo F: Sensitive action → workflow pauses for approval
Demo 8
Enterprise Project, Program & Product Delivery Lab
Problem: Critical milestone slippage is noticed late and executive status reports lag reality.
Experience: Relates to my project coordination, business analysis and Agile delivery roles.
Approach: Intake, charters, requirements, user stories with acceptance criteria, sprints, RAID, change control, UAT and an automated health check (Workflow 4).
- 1. Run Health check → the overdue UAT milestone escalates automatically
- 2. Simulate a delay on another milestone
- 3. Plan a sprint, move stories on the Kanban board, close the sprint with a retro
- 4. Submit a change request and approve it
Demo 9
SAFe Release Train Engineer | Agile Release Train Command Center
Problem: Without visible capacity, dependencies and risks, PI plans overcommit teams and miss cross-team sequencing.
Experience: Relates to my Agile delivery, Scrum ceremonies and program coordination experience.
Approach: WSJF prioritization, breakout planning on a program board, automatic capacity & dependency alerts (Workflow 5), ROAM, confidence vote, commitment, execution tracking and Inspect & Adapt.
- 1. 1-3 Start PI and review WSJF priorities
- 2. 4-8 Assign features to teams/iterations; watch capacity & dependency alerts
- 3. 9-11 Review the program board, resolve conflicts, ROAM risks
- 4. 12-14 Create objectives, vote confidence for all 5 teams, finalize
- 5. 15 Download PI report (Reports)
- 6. 16-17 Complete features, then run Inspect & Adapt
Demo 10
Cybersecurity Incident Response & BCDR Lab
Problem: Response and continuity plans are disconnected, so recovery priorities are unclear during a crisis.
Experience: Relates to my incident response and BCDR governance exposure in GRC roles.
Approach: Severity scoring; critical incidents trigger playbook tasks, escalation, timeline updates and a BCDR impact review against the BIA (Workflow 6).
- 1. Create a Ransomware incident affecting Payments Gateway with regulated data
- 2. Review tasks, escalation and impacted processes
- 3. Advance phases, update tasks, record recovery hours vs RTO
- 4. Record RCA & lessons learned; run a BCDR exercise