Executive Summary
We partnered with Mapped to build an intelligence layer on top of their unified building data fabric. By adding geospatial awareness, predictive analytics, and agentic control, we helped operators achieve 20% energy savings, 22% lower maintenance costs, and 12% better comfort stability—with no hardware replacement or downtime.
The Challenge
Building operators collect massive amounts of telemetry but struggle to act on it. Data platforms normalize streams from BMS, HVAC, and sensors, but they don’t answer the critical questions: What matters most? Where? Why?
Without spatial context, predictive reasoning, or closed-loop control, building data stays passive. Teams see the numbers but can’t turn them into decisions.
Our Approach
We don’t replace existing systems—we extend them. Our team brings 25+ years of experience across GIS, IoT, supply chain optimization, and applied ML/AI. We build the intelligence layer that sits above data fabrics, turning connected data into actionable insights.
Working through Mapped’s API, we designed a four-layer framework:
- Integration Layer — Unifies Mapped telemetry with legacy BMS, CMMS, and utility data
- Smart Context Layer — AI-powered tagging and semantic search reveal relationships across sensors, zones, and usage patterns
- Analytics Layer — Real-time spatial dashboards and predictive models expose anomalies, energy drift, and comfort variance
- Agentic Layer — Operators and automation agents act directly on insights through our Pre-Flight + Undo architecture for safe, reversible control
We anchor every metric in real-world coordinates using GIS mapping. Occupancy analytics show resource intensity per person. Predictive maintenance flags issues before they cause downtime. External context—weather, mobility, tariffs—helps anticipate load and calculate precise ROI.
Results
| Metric | Improvement | Detail |
| Energy Efficiency | 17 – 22% reduction | modeled across pilot portfolios |
| Maintenance Cost | ≈ 20% decrease | Predictive maintenance impact |
| Comfort Stability | ≈ 12% increase | IAQ / temperature variance |
| Downtime | 30 – 35% reduction | Critical equipment uptime gains |
| ESG Reporting Time | ≈ 40% faster | Automated data aggregation |
| Payback Period | < 12 months | Modeled ROI from verified savings |
Savings were validated through our Ops Log dashboard, which includes confidence indices for every efficiency claim.
Key Lessons
- Normalization is only the start. Real value comes from the intelligence layer that interprets and acts on data.
- Partnership beats replacement. Using vendor APIs cut deployment time 25% and preserved existing infrastructure.
- Context drives engagement. When insights are mapped geospatially and expressed in business terms, both operators and executives engage.
Partner Perspective
“Combining our data fabric with IM Republic’s intelligence and control architecture turned raw building data into live operational insight. Teams now act on issues in hours, not days.”
— Director of Digital Buildings, Mapped
The Bottom Line
By layering GIS, ML/AI, and agentic control on top of vendor-neutral data fabrics, we help portfolio owners see exactly how their buildings perform—and respond in real time.
Our value isn’t just analytics. It’s collaboration. We partner across the ecosystem so every platform performs at its best, creating the connective tissue that transforms insight into action and action into measurable growth.