IDN is a modern CAFM platform with 333 interlocking tables — the data depth, audit history and operational granularity AI agents actually need to make accurate decisions across your facilities portfolio.
Computer-aided facility management (CAFM) software is the system of record for the physical and operational state of a built portfolio. It captures buildings, floors, spaces, equipment, work orders, people, materials, documents and compliance — and the relationships between them.
Where legacy CAFM stops at storage, modern CAFM has to power dashboards and AI agents. That requires deep normalization, status-duration logs, and a semantic layer so every join is meaningful. IDN was built to that standard from the ground up.
Most facility management software wasn't designed for agents. The reasoning layer has caught up; the data layer hasn't.
Wide tables blur work orders, assets and people together. Agents lose accuracy in the joins and hallucinate categories that don't exist.
Without per-status duration logs, AI can't reason about SLA, dwell time or operator behaviour. Most predictions become guesses.
Adding AI on top of a 2010-era schema produces brittle pipelines and answers no one trusts. The data has to be AI-ready by design.
Every operational domain — from portfolio to procurement — shares lookup, status, type, audit and history tables. The model is consistent everywhere.
Countries, regions, cities, properties, buildings, floors, spaces and zones.
Employees, contractors, visitors, org structures, branches, cost centres and roles.
Service requests, work orders, PM schedules, inspections and task lifecycle.
Asset registry, surveys, maintenance history and classification.
Space inventory, occupancy data, zones and capacity planning.
Space moves, new installations, renovations and projects with approval workflows.
Safety inspections, incidents, waste management and environmental tasks.
Inventory, stock, purchase orders and material consumption.
Drawing registers, O&M manuals, certificates and document control.
Daily, weekly, monthly and yearly summary views across all operations.
User roles, dashboards, audit trails, help content and background jobs.
Computer-aided design tools for CAFM — floor plans, drawings and spatial authoring.
Most teams stitch CAFM, CMMS, IWMS, BMS and spreadsheets together. IDN consolidates them into one normalized data model.
Reactive, preventive, project and inspection work — all modelled as tasks with procedure schedules, timesheets, materials and per-status duration logs that make SLA reasoning trivial.
Open Work & MaintenanceHierarchical equipment with criticality, warranty, manufacturer and full maintenance history per asset. The highest-signal source for predictive maintenance models.
Open Equipment & AssetsA normalised portfolio spine — region → country → city → property → building → floor → space → subspace — that every operational record resolves to. Rank, benchmark and roll up across the entire estate.
Open Portfolio & PropertiesSub-space granularity with time-series occupancy logging. Drive chargeback, cleaning routes, hot-desking and capacity simulations from one source of truth.
Open Spaces & OccupancyIncidents, near misses, inspections, permits and corrective actions — fully linked to people and places. Energy and waste signals roll up into the same reporting horizons as cost and SLA.
Open EHS & ComplianceMaterialized summary views span daily to yearly so dashboards stay sub-second across millions of operational rows — cost per m², MTBF, PM compliance, occupancy and more.
Open Reporting & AnalyticsBecause every CAFM entity is normalized and every change is logged, the AI Assistant resolves questions against real joins — not guesses.
Leverage equipment history, logs and condition data to predict failures.
AI agents balance skills, location, workload and SLA requirements.
Space and occupancy data enable smarter planning and chargeback.
Audit trails and task tracking power proactive compliance monitoring.
Ask questions in plain English and get accurate answers instantly.
A side-by-side look at where typical CAFM stops and where an AI-ready data platform has to go.
| Dimension | Typical CAFM | IDN |
|---|---|---|
| Data model depth | 20–60 wide tables | 333 normalized tables, 12,000+ fields |
| Audit history | Last-edited timestamps only | Per-status duration logs on every entity |
| Semantic layer | Stringly-typed statuses & types | Lookup-backed types, statuses and categories |
| Reporting horizons | Day-of dashboards only | Pre-aggregated daily → yearly summary views |
| AI readiness | Bolted on, brittle joins | Designed for AI agents from day one |
| Hierarchy depth | Building → space | Region → country → city → property → building → floor → space → subspace |
333 tables, 12,000+ fields, full audit history. Explore the schema or talk to our partner team about deployments.