The Plain-English
Data Foundation
for Building AI
Transform buildings, assets, spaces, and operations into an AI-ready ecosystem using an open relational architecture designed for humans and machines.
Why Building AI struggles today
The enterprise building stack was built for forms and spreadsheets — not for agents, models, or natural language reasoning.
Proprietary Data Silos
Vendor-controlled formats trap your operational data inside closed systems with no exit path.
Disconnected Systems
BMS, CMMS, BIM, and IoT stacks live in isolation — analytics requires custom pipelines for every join.
Cryptic Legacy Databases
Decades-old schemas with abbreviated column names that neither humans nor LLMs can interpret reliably.
Poor AI Context
Models hallucinate because the underlying data lacks the semantic relationships AI needs to reason.
Open Building
Data Architecture
A foundation engineered from the ground up for the AI era — open, relational, semantically rich, and operator-friendly.
Plain-English Schema
Every table, field, and relationship uses human-readable names. No abbreviations. No tribal knowledge required.
Highly Relational Design
First-class joins across buildings, spaces, assets, people, and work — modeled the way operators actually think.
Data Sovereignty
Your schema, your data, your control. The Open Building Schema means zero vendor lock-in.
AI Optimization
Built so LLMs and agents can read, reason about, and act on operational data without translation layers.
The schema is the prompt
Because relationships are explicit and naming is human, agents can reason about your portfolio without brittle translation layers.
Natural Language Queries
Ask in English. Get answers grounded in your operational truth.
Predictive Maintenance
Forecast asset failure using historical work, sensor, and lifecycle data.
Occupancy Optimization
Right-size space using badge, sensor, and reservation signals.
Compliance Monitoring
Continuous evaluation against EHS, regulatory, and policy requirements.
Workforce Optimization
Match technician skills, location, and load to work in real time.
Intelligent Routing
Auto-dispatch work to the right team based on context and history.
Five layers. One coherent stack.
Every layer is designed around the same semantic model — so context flows from infrastructure all the way up to AI agents and end users.
Applications
Web, mobile, BI, and partner apps
AI Agents
Assistants, copilots, autonomous workflows
Business Logic
Workflows, rules, automations, policies
Open Building Schema
CorePlain-English relational data foundation
Infrastructure Services
Storage, search, events, identity, observability
One schema, ten domains
From property hierarchy to compliance — every operational concept has a first-class place in the schema.
Portfolio & Properties
Sites, buildings, floors, areas.
People & Organizations
Employees, contractors, departments.
Work & Maintenance
Requests, orders, PMs, history.
Equipment & Assets
Lifecycle, hierarchy, condition.
Moves, Adds, Changes
Space planning and transitions.
EHS & Compliance
Permits, inspections, incidents.
Materials & Procurement
Parts, vendors, purchase orders.
Documents
Drawings, manuals, certificates.
Reporting & Analytics
KPIs across all horizons.
System & Security
Roles, audit, governance.
An open standard for the built environment.
Infrastructure.Net sponsors the Open Building Schema — a shared, vendor-neutral data architecture for buildings, assets, and operations. Adopt it, extend it, own it.
Learn About Open Building Schema- Open standard published under permissive license
- Community-driven governance and roadmap
- Developer adoption across PropTech ecosystem
- Customers own their data architecture
From business question to grounded SQL
Because every entity is named like a human would name it, AI can translate operational questions into accurate, joinable queries on the first try.
Which chillers in our Boston portfolio are overdue for PM and over 15 years old?
SELECT a.asset_name, b.building_name, a.install_date,
p.next_due_date
FROM assets a
JOIN buildings b ON a.building_id = b.building_id
JOIN preventive_maintenance p ON p.asset_id = a.asset_id
WHERE a.asset_type = 'Chiller'
AND b.city = 'Boston'
AND a.install_date < NOW() - INTERVAL '15 years'
AND p.next_due_date < NOW();Show me high-occupancy floors where workplace satisfaction dropped this quarter.
SELECT f.floor_name, AVG(o.occupancy_rate) AS avg_occ,
AVG(s.satisfaction_score) AS sat
FROM floors f
JOIN occupancy_metrics o ON o.floor_id = f.floor_id
JOIN satisfaction_surveys s ON s.floor_id = f.floor_id
WHERE o.captured_at >= date_trunc('quarter', NOW())
GROUP BY f.floor_name
HAVING AVG(o.occupancy_rate) > 0.8
AND AVG(s.satisfaction_score) < 3.5;A growing network of expert builders
Infrastructure.Net is delivered through a curated ecosystem of partners across consulting, integration, and technology.
Consultants
Strategy, advisory, change management
Integrators
Implementation and systems integration
Developers
ISVs building on the Open Building Schema
Technology Partners
BMS, BIM, IoT, identity, and analytics
Build the future of Building Intelligence
See the platform in action with a tailored demonstration for your portfolio.