Mapped is the independent data layer for commercial real estate. By automating the discovery, extraction, and normalization of data from building systems, sensors, devices, and vendor APIs, Mapped simplifies the integration process down to a single standardized API. Mapped breaks enterprise data silos to empower building owners, facility operators, and solution providers to rapidly unlock the value of data and drive transformative business outcomes – allowing them to focus on innovation rather than integration.
Mapped started with the idea “what if every built space had an API?” Getting data out of buildings was a complex, time consuming and often manual process - weeks or even months of work. To solve the problem, they created a knowledge graph of people, places and things using machine learning to automate the process of data extraction and identification. They then built a simple, secure and unified API on top; now anything that generates data - devices, sensors, enterprise applications and more - is accessible quickly, easily and securely.
Check out their website to learn more: https://www.mapped.com/
Morgan Stanley uses network micro-segmentation and automated tagging as a "golden template" across its OT network so that hacked devices cannot laterally hop to other systems.
Hannah Baker, engineer at Willow, walks through how DFW Airport built a CBM program that actually stuck, from training a non-technical QA team to triage thousands of faults, to graduating recurring issues into automated work orders, to tracking a single KPI called 'unsuccessfully actioned' that finally gave leadership visibility into whether closed work orders were actually fixing the problem.
Jose de Castro, CTO of Mapped, shows how one of the world's largest retailers moved restroom operations from schedule-based janitorial rounds to condition-based workflows by combining foot traffic sensors, flush counts, soap levels, and occupancy predictions into AI-summarized work orders that land directly in the existing CMMS, with no new dashboards or tools for technicians to learn.
Brad Dameron from the University of Iowa's Asset Optimization Team and Katie Rossman from Clockworks Analytics walk through how Iowa handles 3,500 faults per day without burying their maintenance shops, showing the exact triage, routing, and closeout workflow they built to turn fault detection into planned work orders that look and feel identical to every other work order in the system.
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