CASE STUDY
Advancing Trust in AI-Enabled Smart Building Operations
How Omniconn used UL 3115 AI safety certification to demonstrate a structured approach to AI safety, transparency, governance and human oversight.
Complex commercial campuses, government facilities and mission-critical environments depend on multiple systems working together effectively.
Building management systems, HVAC infrastructure, fire and life-safety systems, IoT sensors, energy meters and operational workflows often operate across fragmented environments. This can make it difficult for facility teams to maintain clear visibility, respond consistently to changing conditions and identify inefficiencies before they affect operations.
At the same time, organizations face increasing pressure to:
While facilities generate significant volumes of data, data alone does not always provide actionable intelligence.
Teams may struggle to understand how changing weather conditions, equipment performance, occupancy patterns and building systems interact in real time.
As AI becomes increasingly involved in operational decision-making, another challenge emerges:
How can organizations trust AI-enabled systems operating within high-consequence building environments?
Stakeholders increasingly expect more than product claims or stated AI principles. They require evidence that AI-enabled functionality is governed, transparent, secure and subject to meaningful human oversight.
Based in the United Arab Emirates, Omniconn is an IoT platform provider specializing in intelligent building solutions.
The company connects physical infrastructure—including:
—into a centralized platform for monitoring, analysis and control.
Omniconn Platform 4.0 is designed to support:
Improved visibility across connected infrastructure and critical operational systems.
AI-assisted insights that help teams identify deviations and opportunities for optimization.
More informed decisions around energy and resource consumption.
AI recommendations that remain subject to operator review, approval, modification or rejection.
Consider a warm-climate office building.
Outdoor temperatures begin rising earlier than forecast. Sun-exposed zones warm faster than historical patterns, increasing cooling demand.
Omniconn analyzes real-time inputs from:
Rather than relying solely on fixed schedules or static rules, the platform identifies meaningful deviations from expected operating conditions.
It can then provide targeted recommendations, such as:
Recommendations are presented through a centralized dashboard with supporting context.
Operators can understand:
What is happening.
Which zones or assets are affected.
How current conditions compare with historical patterns.
What action is being recommended.
Most importantly, facility teams remain in control.
Operators can review, approve, modify or decline recommendations based on operational priorities, occupant comfort or scheduling requirements.
As Omniconn expanded the role of AI across connected building environments, the organization wanted to demonstrate that its AI-enabled functionality could be independently evaluated against recognized safety requirements.
The decision to pursue certification was not driven solely by customer demand.
It reflected a broader commitment to responsible AI deployment in environments where safety, resilience and operational continuity matter.
“We had conviction in our platform, but in mission-critical environments, evidence is what matters.”
— Saleem Syed
Head of Architecture and Advisory, Omniconn
The company sought an independent, third-party process capable of evaluating AI-enabled functionality across technical, ethical and governance considerations.
UL Solutions worked with Omniconn to complete a third-party evaluation to UL 3115, the Outline of Investigation for Safety of AI-Based Products.
UL 3115 provides a structured, evidence-based framework for evaluating AI-based products.
The evaluation includes:
The objective is to evaluate how AI systems are:
Designed.
Developed.
Deployed.
Governed.
For Omniconn, the system-level evaluation examined how AI-enabled functionality is designed, governed and controlled when influencing operations across integrated building environments.
The evaluation moved beyond high-level AI principles to examine how the platform operates in practice.
UL Solutions evaluated whether Omniconn Platform 4.0 demonstrated appropriate considerations across key areas.
Assessment of how the platform operates as AI-enabled functionality and autonomy increase across building operations.
Evaluation of whether operators can understand AI-generated insights, recommendations and supporting context.
Assessment of safeguards that enable operators to:
Evaluation of governance controls supporting the management and oversight of AI behavior across the platform.
Assessment of relevant cybersecurity considerations for AI-enabled operations.
Evaluation of safety and performance considerations relevant to integrated smart building environments.
“As AI moves from analysis into real-world control of energy and building systems, independent safety evaluation becomes essential to earning trust. UL 3115 provides an evidence-based approach for evaluating adaptive, learning systems in mission-critical environments.”
— Alberto Uggetti
Executive Vice President, Commercial Excellence
UL Solutions
Upon successful completion of the evaluation, Omniconn earned UL 3115 AI safety certification for Omniconn Platform 4.0.
Omniconn Platform 4.0 became the world's first AI-enabled smart building platform to achieve UL 3115 AI safety certification.
The achievement also marked Omniconn as the first recipient of AI safety certification from UL Solutions.
The successful evaluation demonstrated that the platform met applicable safety requirements across relevant technical, ethical and governance considerations.
Following certification, Omniconn's application became eligible to use the widely recognized UL Mark.
The certification provides an independent reference point demonstrating that relevant safety considerations were evaluated through a structured third-party process.
For stakeholders, this can help support conversations around:
The impact of the UL 3115 evaluation extended beyond the certification itself.
Omniconn describes the process as helping formalize how the organization approaches AI safety and governance.
Before the evaluation, many AI safety practices were already embedded in product development and engineering processes.
The certification process required these practices to become more explicit and traceable through documented evidence.
This helped clarify:
Who is responsible for AI-related risk and governance decisions?
How are AI limitations documented and communicated to operators?
How are governance decisions recorded and maintained?
How can AI safety practices remain aligned across architecture, product, engineering and operations?
The process encouraged cross-functional alignment and helped establish clearer accountability structures.
Certification is not simply a one-time milestone.
The discipline of documenting AI limitations, evaluating risks and maintaining evidence can support a more structured approach to future product development.
As Omniconn develops new AI-enabled capabilities, the organization can apply lessons from the evaluation process to:
This creates a foundation for continued innovation while maintaining attention to safety, transparency and accountability.
Buildings are becoming increasingly connected and intelligent.
AI has the potential to help organizations improve:
However, as AI moves closer to operational decision-making and control, trust becomes increasingly important.
Omniconn's UL 3115 certification provides an independently evaluated foundation for advancing AI-enabled building intelligence in environments where safety and operational continuity matter.
By combining connected infrastructure, AI-assisted intelligence and meaningful human oversight, Omniconn aims to help organizations create building environments that are:
Connected systems working together to provide actionable operational insights.
Data-driven optimization supporting better energy and resource management.
Improved visibility across complex and mission-critical infrastructure.
AI-generated recommendations supported by meaningful operational context.
AI-enabled capabilities supported by structured safety, governance and oversight considerations.
For organizations adopting AI across critical building operations, confidence in technology must be supported by evidence.
Omniconn's successful evaluation to UL 3115 demonstrates how AI-enabled smart building platforms can pursue a structured approach to safety, transparency, cybersecurity, accountability and human oversight.
As intelligent infrastructure continues to evolve, independent evaluation can play an important role in helping organizations understand and communicate how AI systems are designed and governed.
Omniconn Platform 4.0 represents a step toward a future where smarter buildings are not only more connected and efficient—but also more transparent, resilient and trustworthy.
Complex commercial campuses, government facilities and mission-critical environments depend on multiple systems working together effectively.
Building management systems, HVAC infrastructure, fire and life-safety systems, IoT sensors, energy meters and operational workflows often operate across fragmented environments. This can make it difficult for facility teams to maintain clear visibility, respond consistently to changing conditions and identify inefficiencies before they affect operations.
At the same time, organizations face increasing pressure to:
While facilities generate significant volumes of data, data alone does not always provide actionable intelligence.
Teams may struggle to understand how changing weather conditions, equipment performance, occupancy patterns and building systems interact in real time.
As AI becomes increasingly involved in operational decision-making, another challenge emerges:
How can organizations trust AI-enabled systems operating within high-consequence building environments?
Stakeholders increasingly expect more than product claims or stated AI principles. They require evidence that AI-enabled functionality is governed, transparent, secure and subject to meaningful human oversight.
Based in the United Arab Emirates, Omniconn is an IoT platform provider specializing in intelligent building solutions.
The company connects physical infrastructure—including:
—into a centralized platform for monitoring, analysis and control.
Omniconn Platform 4.0 is designed to support:
Improved visibility across connected infrastructure and critical operational systems.
AI-assisted insights that help teams identify deviations and opportunities for optimization.
More informed decisions around energy and resource consumption.
AI recommendations that remain subject to operator review, approval, modification or rejection.
Consider a warm-climate office building.
Outdoor temperatures begin rising earlier than forecast. Sun-exposed zones warm faster than historical patterns, increasing cooling demand.
Omniconn analyzes real-time inputs from:
Rather than relying solely on fixed schedules or static rules, the platform identifies meaningful deviations from expected operating conditions.
It can then provide targeted recommendations, such as:
Recommendations are presented through a centralized dashboard with supporting context.
Operators can understand:
What is happening.
Which zones or assets are affected.
How current conditions compare with historical patterns.
What action is being recommended.
Most importantly, facility teams remain in control.
Operators can review, approve, modify or decline recommendations based on operational priorities, occupant comfort or scheduling requirements.
As Omniconn expanded the role of AI across connected building environments, the organization wanted to demonstrate that its AI-enabled functionality could be independently evaluated against recognized safety requirements.
The decision to pursue certification was not driven solely by customer demand.
It reflected a broader commitment to responsible AI deployment in environments where safety, resilience and operational continuity matter.
“We had conviction in our platform, but in mission-critical environments, evidence is what matters.”
— Saleem Syed
Head of Architecture and Advisory, Omniconn
The company sought an independent, third-party process capable of evaluating AI-enabled functionality across technical, ethical and governance considerations.
UL Solutions worked with Omniconn to complete a third-party evaluation to UL 3115, the Outline of Investigation for Safety of AI-Based Products.
UL 3115 provides a structured, evidence-based framework for evaluating AI-based products.
The evaluation includes:
The objective is to evaluate how AI systems are:
Designed.
Developed.
Deployed.
Governed.
For Omniconn, the system-level evaluation examined how AI-enabled functionality is designed, governed and controlled when influencing operations across integrated building environments.
The evaluation moved beyond high-level AI principles to examine how the platform operates in practice.
UL Solutions evaluated whether Omniconn Platform 4.0 demonstrated appropriate considerations across key areas.
Assessment of how the platform operates as AI-enabled functionality and autonomy increase across building operations.
Evaluation of whether operators can understand AI-generated insights, recommendations and supporting context.
Assessment of safeguards that enable operators to:
Evaluation of governance controls supporting the management and oversight of AI behavior across the platform.
Assessment of relevant cybersecurity considerations for AI-enabled operations.
Evaluation of safety and performance considerations relevant to integrated smart building environments.
“As AI moves from analysis into real-world control of energy and building systems, independent safety evaluation becomes essential to earning trust. UL 3115 provides an evidence-based approach for evaluating adaptive, learning systems in mission-critical environments.”
— Alberto Uggetti
Executive Vice President, Commercial Excellence
UL Solutions
Upon successful completion of the evaluation, Omniconn earned UL 3115 AI safety certification for Omniconn Platform 4.0.
Omniconn Platform 4.0 became the world's first AI-enabled smart building platform to achieve UL 3115 AI safety certification.
The achievement also marked Omniconn as the first recipient of AI safety certification from UL Solutions.
The successful evaluation demonstrated that the platform met applicable safety requirements across relevant technical, ethical and governance considerations.
Following certification, Omniconn's application became eligible to use the widely recognized UL Mark.
The certification provides an independent reference point demonstrating that relevant safety considerations were evaluated through a structured third-party process.
For stakeholders, this can help support conversations around:
The impact of the UL 3115 evaluation extended beyond the certification itself.
Omniconn describes the process as helping formalize how the organization approaches AI safety and governance.
Before the evaluation, many AI safety practices were already embedded in product development and engineering processes.
The certification process required these practices to become more explicit and traceable through documented evidence.
This helped clarify:
Who is responsible for AI-related risk and governance decisions?
How are AI limitations documented and communicated to operators?
How are governance decisions recorded and maintained?
How can AI safety practices remain aligned across architecture, product, engineering and operations?
The process encouraged cross-functional alignment and helped establish clearer accountability structures.
Certification is not simply a one-time milestone.
The discipline of documenting AI limitations, evaluating risks and maintaining evidence can support a more structured approach to future product development.
As Omniconn develops new AI-enabled capabilities, the organization can apply lessons from the evaluation process to:
This creates a foundation for continued innovation while maintaining attention to safety, transparency and accountability.
Buildings are becoming increasingly connected and intelligent.
AI has the potential to help organizations improve:
However, as AI moves closer to operational decision-making and control, trust becomes increasingly important.
Omniconn's UL 3115 certification provides an independently evaluated foundation for advancing AI-enabled building intelligence in environments where safety and operational continuity matter.
By combining connected infrastructure, AI-assisted intelligence and meaningful human oversight, Omniconn aims to help organizations create building environments that are:
Connected systems working together to provide actionable operational insights.
Data-driven optimization supporting better energy and resource management.
Improved visibility across complex and mission-critical infrastructure.
AI-generated recommendations supported by meaningful operational context.
AI-enabled capabilities supported by structured safety, governance and oversight considerations.
For organizations adopting AI across critical building operations, confidence in technology must be supported by evidence.
Omniconn's successful evaluation to UL 3115 demonstrates how AI-enabled smart building platforms can pursue a structured approach to safety, transparency, cybersecurity, accountability and human oversight.
As intelligent infrastructure continues to evolve, independent evaluation can play an important role in helping organizations understand and communicate how AI systems are designed and governed.
Omniconn Platform 4.0 represents a step toward a future where smarter buildings are not only more connected and efficient—but also more transparent, resilient and trustworthy.
