Onboard is how building experts talk to buildings. The only self-serve AI platform for connecting and communicating with your buildings and its equipment.
Building Energy and Optimization Engineers use Onboard’s AI software to acquire the building data they need to improve their client’s buildings. Onboard’s self-serve AI software enables any engineer to collect, standardize, visualize, and share building data across their team or analytical apps. Engineers can flexibly install Onboard’s virtualized software on their IT’s preferred hardware inside the building’s network. Currently, Onboard is focused on BACnet and Modbus data.
Onboard’s AI filters out irrelevant data and applies standard ontologies, including Project Haystack Tags and Google’s Digital Buildings Ontology. Onboard transparently shares how its AI achieved its predictions, which allows engineers to intuitively operate its AI and all other software operations entirely by themselves.
Engineers can export their data to CSV, JSON or use Onboard’s REST API to pipe data to any application. Onboard provides Python and R SDKs for engineers seeking to flex their data science skills as well as an ongoing YouTube Series and Knowledge Base for how to creatively use your building data.
Onboard’s uniquely lightweight approach makes Onboard attractive to smart building consultants and OEMs alike, anyone needing a scalable, transparent and a cost-effective method for normalizing building data across portfolios. Onboard is an enabler of use-cases; its mission is to equip every engineer with the data they need to improve the world’s buildings.
Stanford University discovered multiple data accuracy challenges as they migrated from a decade-old utility data historian. Now, the university is building a point-level data standards document to restore stakeholder confidence in its energy data.
CannonDesign watched a BAS access quote climb from $66K to $100K, then brought in an MSI to review the architecture and cut it to $29K.
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