System design
How AI FlowOps turns State Benefits Portal Modernization into a governed business decision
The public Case Room is a read-only guided demo of a completed AI-processed workflow. It shows the same operating pattern the backend supports: opportunity screening, intake, extraction, specialist routing, human review, synthesis, decision logging, and KPI capture.
Opportunity Discovery / AI ScreeningMonitor feeds, download notices, filter likely contract-fit RFPs
Document InputsRFPs, contracts, notes
Ingestion LayerParse and normalize
AI Decision EngineExtract, classify, recommend
Workflow EngineRules, routes, packets
Specialist HITL LayerLegal, Security, Finance, Implementation
AI Synthesis LayerCollate reviews and prepare BD/Ops packet
BD/Ops HITL LayerOwn final bid/no-bid decision
Database / Audit LogCases, events, traces
Dashboard LayerKPIs and proof views
Technical stack
- FrontendServer-rendered Jinja templates and repo-owned CSS
- BackendFastAPI application routes and workflow APIs
- DatabaseSQLite persistence for cases, traces, approvals, and KPIs
- AI workflowAI processes the source documents into screening, analysis, packets, and synthesis; public pages display the completed run read-only
Deployment flow
Local Development
GitHub
GitHub Actions
Private VM Demo
What this proves
Product design
End-to-end operations workflow One business question moves through AI, specialists, BD/Ops, and audit records.AI system design
Grounded decisions Every major claim links back to a source phrase and an extracted fact.Workflow automation
Department-specific packets The AI generates different packets for Legal, Security, Finance, and Implementation.Governance
Human-owned decision AI recommends; specialist reviewers and BD/Ops own the final decision.