Multimodal Sensor Integration
Thermal occupancy sensors, air quality monitors, motion detectors, dispenser level sensors, and trash bin sensors create a holistic, real-time understanding of building environments including restroom facilities.

Our intelligent multimodal AI platform is designed to revolutionize cleaning and operational processes across diverse real estate verticals—from offices and airports to healthcare and educational institutions. It seamlessly integrates real-time sensor data, advanced machine learning, and powerful LLMs to understand and optimize building needs. Furthermore, the platform integrates with existing CMMS systems for seamless work order management, connects with workforce management tools for optimized staff scheduling and task allocation, and extends its capabilities to document editing, including client reports, RFP responses, compliance documentation, and proposal writing, all tailored to each building's unique data and industry expertise. Beginning with comprehensive cleaning optimization and smart restroom management, it expands to specialized, privacy-first monitoring and predictive maintenance, creating spaces that anticipate needs, self-optimize, and achieve unprecedented efficiency.
Deployment focuses on revolutionizing cleaning operations through privacy-first sensors and intelligent scheduling. The system anonymously detects occupancy patterns in spaces like conference rooms, lobbies, and restrooms, enabling precise sanitization when and where it's needed most—reducing costs while ensuring consistently hygienic spaces. Leading solutions like Zan Compute thermal sensors provide anonymous occupancy detection, while AI-powered platforms deliver natural language recommendations that facility managers can immediately understand and implement. This ensures consistently clean and pleasant facilities, reduces unnecessary checks, and optimizes staff deployment, leading to significant efficiency gains and improved user satisfaction for both general areas and dedicated restroom management.
Enterprise-grade security and absolute data isolation are foundational to our platform. All client data and associated machine learning models are rigorously sandboxed, ensuring zero cross-contamination. Your proprietary building data is processed within its own secure environment, guaranteeing complete confidentiality and preventing any form of information sharing or unintended leakage across organizations. We adhere to the highest industry standards for data governance and protection.
Thermal occupancy sensors, air quality monitors, motion detectors, dispenser level sensors, and trash bin sensors create a holistic, real-time understanding of building environments including restroom facilities.
Deep learning processes sensor data while LLMs deliver natural language insights instantly, turning raw data into actionable intelligence.
Buildings automatically optimize cleaning, restocking, and maintenance schedules based on context, seasonality, and occupancy patterns.
Our multimodal AI platform offers transformative analytical power, but it's crucial to understand its designed scope and inherent dependencies for optimal use. We champion transparency, ensuring our clients can confidently leverage AI's strengths while understanding where human expertise remains paramount.
Seamless Data Interaction: Interact naturally with your building data and extract actionable intelligence from sensor, CMMS, and audit information.
Real-time Processing: Swiftly analyze data streams, forecast outcomes based on historical data.
RFP Analysis & Response: Analyze janitorial RFPs; generate tailored responses using building data.
Expert Knowledge Base: Answer complex questions from infection control standards to detailed restroom SOPs.
CMMS Integration: Seamlessly connects with existing CMMS platforms to automate work order generation and track maintenance tasks.
Workforce Management: Optimizes staff scheduling and task allocation based on real-time building needs and occupancy patterns.
Specialized Focus: AI for janitorial processes and building operations only—it cannot help plan your vacation.
Privacy Boundaries: Operates strictly within ethical and data privacy guidelines.
Data Dependency: Effectiveness directly tied to input data availability and quality.
Our intuitive dashboard transforms complex sensor data into actionable, natural language insights. Facility managers receive real-time alerts and recommendations, allowing for proactive decision-making without needing deep technical expertise.
High traffic detected in West Wing restrooms (floors 3-5). Recommend immediate spot cleaning to maintain hygiene standards.
Based on current air quality and projected occupancy, a deep clean for the main lobby is due tonight. Staff allocation has been optimized.
Supply levels in all high-traffic restrooms are consistently below 30% by end-of-day. Suggest increasing reorder frequency for paper towels and soap.
Optimized cleaning schedules and predictive maintenance reduce operational expenses
Anonymous sensing ensures complete occupant privacy while gathering actionable data
Our multimodal AI platform seamlessly integrates with robotic cleaning equipment, coordinating their operations with real-time building data. This enables intelligent dispatch and optimized route planning for maximum efficiency. Cleaning robots are deployed precisely when and where needed, based on occupancy patterns and cleaning requirements detected by our comprehensive sensor network. This dynamic coordination ensures that cleaning resources are always focused on high-traffic or high-need areas, minimizing energy consumption and maximizing cleanliness.
The convergence of sensor ML and LLM technologies represents the most significant advancement in building management in decades. Buildings no longer just respond—they anticipate, communicate, and optimize themselves intelligently
LLMs translate complex sensor data into clear, conversational insights that facility managers can immediately understand and act upon—no technical expertise required.
The platform doesn't just detect conditions—it understands context, seasonality, and patterns to make intelligent recommendations that consider the full building ecosystem.
Machine learning models improve over time, adapting to unique building characteristics and usage patterns to deliver increasingly optimized performance.
Deploy intelligent cleaning automation with occupancy-based scheduling and real-time sanitization alerts.
Integrate climate control with occupancy data for zone-specific temperature and airflow management
Add adaptive lighting systems that respond to natural light levels and occupancy patterns
Scale to full building management ecosystem with predictive maintenance and unified control
Cut operational expenses by 20% through optimized resource allocation, automated scheduling, and predictive maintenance that prevents labor wastage and costly equipment failures.
Ensure consistently sanitized spaces with real-time air quality monitoring and automated cleaning triggers—critical for occupant wellbeing and regulatory compliance.
Meet environmental targets with precision energy management, reduced waste from optimized resource use, and comprehensive ESG reporting capabilities.
Boost satisfaction and productivity with perfectly calibrated environments that automatically adapt to usage patterns and individual zone requirements.