Department AI & Automation Hub
A role-aware internal hub for AI assistants, operational connectors, scheduled automations, analytics, and department-specific workflows.
01 / The problem
What needs to change
Teams accumulate disconnected automations, provider credentials, forms, work trackers, reporting routines, and AI experiments without a clear operating surface or shared governance model.
02 / The approach
A focused path through the complexity
The product organizes tools by department, centralizes connector setup, and combines retrieval-grounded assistants with role-gated scheduled workflows and visible diagnostics.
03 / Key capabilities
What the system is designed to do
- Department-specific tool and automation workspaces
- Custom assistant studio with document retrieval and streaming chat
- Connector catalog with masked credentials and health checks
- Scheduled people-operations and reporting automations
- Executive variance analytics and governed manual-run controls
04 / Architecture
Technology and system shape
- React and Vite frontend with an Azure Functions backend
- Static Web Apps identity mapped to application roles
- Connector-first integration layer with environment fallback
- Responses-based assistant runtime with retrieval and structured outputs
- Durable idempotency and dry-run safeguards for scheduled workflows
05 / Results
What the repository demonstrates
- The repository implements a working multi-department shell with assistants, connectors, automation controls, diagnostics, and analytics.
- Sensitive actions are bounded by roles, dry-run modes, signatures, idempotency, and explicit operator triggers.
06 / Lessons
What the work teaches
- Internal AI adoption improves when assistants and automations share one connector and permission model.
- Operational readiness must be visible before a scheduled workflow is allowed to act.
07 / Screenshots
Approved visuals
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