Nexus Platform

Our Nexus Platform integrates Internet of Things and Artificial Intelligence/Machine Learning driven data collection with legacy building management systems for optimal energy and cost savings, as well as effective operational management.

A smart platform integrating legacy building systems, Internet of Things and Smart Building applications together. The Nexus Platform automates information extraction and metadata tagging of unstructured data using the Haystack and Brick Open Standards. Nexus APIs provide interfaces to any Building System and Internet of Things System.



  • Increases speed of deploymentncreases speed of deployment
  • Reduces human effort and error in data extraction
  • Significant cost reduction in data extraction, integration and reuse

Nexus Analytics

Our suite of Artificial Intelligence driven analytics for Smart Buildings, includes Energy Avoidance Analytics, Fault Diagnostics and Predictive Analytics.

Together with the Nexus Data Integration Platform and the Nexus NLP Query engine, it forms an integrated solution suite specifically designed for Smart Buildings.



  • Analysis that provides actionable recommendations

  • Immediate benefits with prioritise list of cost benefit implementation

  • Artificial Intelligence/Machine Learning driven capabilities


Nexus Mobile

Our intelligent mobile solution understands natural human language queries. It overcomes the limitations of traditional dashboards to perform online query of Building OT systems (BAS, EMS, CMMS, IoT, etc).



  • Increases operational efficiency
  • Increases customer and stakeholder satisfaction
  • Scalable and easy to maintain

Nexus Auto Tagging

Nexus Auto Tagging is a modern approach to building automation system point tagging using Artificial Intelligence/Machine Learning technologies.

Old methods of tagging information requires the use of manual or algorithmic approaches. This requires knowledgeable professionals and lacks scalability.

Nexus Auto Tagging uses advanced technology such as Artificial Intelligence/Machine Learning and knowledge gathered from experience with dozens of companies spanning numerous different systems.



  • Consistency in naming and tagging
  • Greater accuracy in identifying points
  • Uses standardized set of tags based on the Haystack and Brick Standards
  • Limited requirement in human intervention¬†