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 Onboardās AI software to acquire the building data they need to improve their clientās buildings. Onboardās 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 Onboardās virtualized software on their ITās preferred hardware inside the buildingās network. Currently, Onboard is focused on BACnet and Modbus data.
Onboardās AI filters out irrelevant data and applies standard ontologies, including Project Haystack Tags and Googleās 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 Onboardās 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.
Onboardās 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 worldās buildings.
Lincoln Property Companyās Chris Lelle realized that burdened engineers canāt each manage 300,000 sq ft by diving deep into BAS dataāso he used FDD to simplify the troubleshooting his techs need to do.
For years, complaints about comfort at a Microsoft campus were attributed to BAS issues. Packet-level network data told a different story and exposed 118,000 hours of missed runtime.
Goldman Sachs detailed how it scaled a global smart building program across 94 sites by changing where cybersecurity decisions happenābefore devices ever reach the field.
Despite hefty efficiency and sustainability goals, Databank faces a recurring hurdle: customers fear that AI-driven or automated BMS sequences might compromise critical uptime.
Delta Air Lines and JLL made a deliberate call at LaGuardia Terminal C: stop relying on engineers to walk rooms multiple times a day just to confirm conditions were still acceptableāand replace those rounds with standardized, proactive alerting.
Five years ago, Clockworks Analytics made a bet: fault detection would only reach most commercial buildings if it could work without deep owner-side engineering teams.
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