Layer 1
Data & Skill Intelligence Layer
Aggregates structured and unstructured skill data from HRIS, learning platforms, and project repositories; normalizes into a unified skill taxonomy.
- Skill ontology (technical, domain, soft skills)
- Real‑time skill inventory updates
- Confidence scoring for skill relevance
Layer 2
AI Matching & Optimization Engine
Applies machine‑learning models to match people to work based on skill fit, availability, past performance, and diversity goals.
- Constraint‑based optimization (capacity, compliance, cost)
- Predictive performance scoring
- What‑if scenario simulation
Layer 3
Governance & Policy Layer
Enforces enterprise policies—role‑based access, regulatory constraints, and diversity mandates—through rule‑sets that the AI engine respects.
- Policy rule engine (e.g., GDPR, SOX, internal staffing policies)
- Audit trail of team‑formation decisions
- Approval workflow for exception handling
Layer 4
Integration & Execution Layer
Connects to project management, collaboration, and resource‑planning tools to provision teams automatically and provide ongoing monitoring.
- Bi‑directional sync with Jira, Azure DevOps, ServiceNow
- Automated onboarding/off‑boarding triggers
- Live utilization & health dashboards
Layer 5
Operational Oversight & Continuous Improvement
Provides IT‑operations visibility and feedback loops to refine models, update skill data, and measure business outcomes.
- KPIs: time‑to‑staff, skill‑gap reduction, team utilization
- Model retraining cadence
- Root‑cause analysis of staffing anomalies