A six-layer AI-enabled HR architecture for globally distributed organisations operating across multiple jurisdictions with complex compliance and hyper-growth requirements.
Most HR data architectures in scaling organisations are fragmented by design: separate tools for incident management, payroll, performance, and analytics that never truly converge. The result is delayed intelligence, inconsistent policy application, and leadership operating on stale or incomplete data.
PRIF eliminates this by consolidating Employee Relations, Performance Management, Absence Management, and Conduct Compliance into a single unified, real-time intelligence platform — governed by a proprietary severity-scoring model and surfaced through embedded AI.
The architecture was designed specifically for organisations with distributed workforces across multiple jurisdictions, where manual compliance management creates both legal exposure and operational drag at scale.
The proprietary Employee Non-Compliance (ENC) Model automatically assigns legally-aligned severity scores (1–3) to all conduct, performance, absence, and self-reported events. Consistent global policy application without manual HR judgement at point of incident.
Generative AI layer (Claude API / Microsoft Copilot) provides predictive attrition modelling, compliance risk alerts, and natural language investigation summaries. Executive-level insights without requiring SQL or BI tool expertise.
The HRIS serves as the operational interface for all credentialed users with embedded Power BI dashboards via custom tabs. Line managers, HR Business Partners, and C-suite each see role-appropriate views — all within one system, governed by Row-Level Security.
Microsoft Fabric replaces traditional ETL pipelines, separate data warehouse infrastructure, and middleware layers in a single unified platform. Estimated 40% reduction in data infrastructure costs while improving data freshness and query performance.
Each layer serves a distinct function. OrgVue sits upstream as an optional strategic input rather than a numbered layer; operational data capture runs across Layers 1–3; intelligence and analytics at Layers 4–6. The architecture operates on a 24-hour sync cycle, with overnight batch processing providing compliance-grade data freshness.
Workforce planning and scenario modelling foundation. Used at strategic inflection points — restructuring, growth planning, M&A — not daily operations. Provides the organisational canvas on which all downstream data is mapped.
Custom HRIS forms and workflows capture atypical conduct and performance events — including serious incident reports, self-declared criminal convictions, and non-work vehicular convictions. Eliminates dependency on external form platforms.
Proprietary scoring engine mapping all conduct, capability, absence, and self-reported events to a standardised 1–3 severity scale. Grounded in employment law precedent and Employment Tribunal case authority. Ensures consistent global policy application and full audit trail of all scoring decisions.
Employer of Record and global payroll system with native bi-directional HRIS integration. Provides cost data, tenure metrics, and employment status for compliance modelling and P&L workforce planning across multiple jurisdictions.
Central HRIS as operational interface and single source of truth. Provides role-based access to individual employee records, department analytics, and embedded Power BI dashboards via custom tabs. The ENC severity score is written back here, enabling managers to view compliance status without accessing BI tools directly.
Unified data platform. Fabric OneLake ingests data from HRIS and EOR, applies ENC scoring logic, and serves Power BI via Direct Lake for sub-second dashboard refresh. Replaces traditional ETL pipelines, Azure SQL, and middleware. Row-Level Security propagates from Fabric to embedded dashboards automatically.
Generative AI services layered on the analytics platform for predictive attrition modelling, natural language investigation summaries, compliance risk forecasting, and automated pattern detection. Surfaces executive-level intelligence without requiring SQL or BI expertise from leadership.
| Source | Destination | Data Type & Purpose |
|---|---|---|
Layer 4 → 5 HRIS |
Microsoft Fabric |
Incident reports, custom form submissions, absence records, performance review outcomes, self-reported events, SIR/GIR investigation records. |
Layer 3 → 4 EOR / Payroll |
HRIS |
Native bi-directional sync of new hires, terminations, salary changes, cost centre allocations, and tenure metrics. Maintained as single employment record. |
Layer 3 → 5 EOR / Payroll |
Microsoft Fabric |
Cost analytics: headcount costs, FTE data, contractor spend, and benefits costs for P&L modelling and workforce planning. |
CRITICAL · Layer 5 → 4 Microsoft Fabric |
HRIS (Reverse Flow) |
Fabric applies ENC model logic, assigns 1–3 severity scores, then writes scores back to HRIS custom fields. Enables managers to view individual compliance status directly in the HRIS without BI tool access. |
Layer 5 → 5 Microsoft Fabric |
Power BI |
Direct Lake connection reads Delta Parquet files from Fabric OneLake without traditional import/refresh cycles. Near real-time dashboard updates with in-memory query performance. |
Layer 5 → 4 Power BI |
HRIS (Embedded) |
Power BI reports embedded as custom tabs in HRIS. URL parameter filtering enables automatic per-employee or per-department scoping. Row-Level Security ensures appropriate access at all levels. |