Automations
This pillar focuses on building operations workflows that adjust HVAC, lighting, access, and maintenance based on occupancy, energy pricing, and asset condition. The content should show how custom property automation lowers operating cost, improves tenant experience, and integrates predictive maintenance with modern building management systems.
This foundational page outlines a custom orchestration architecture that integrates HVAC, lighting, access, and maintenance systems into a unified, predictive operational layer. It details how multi-agent workflows reduce energy costs, improve tenant satisfaction, and automate compliance by connecting IoT data, BMS controls, and CMMS platforms. The implementation blueprint covers data ingestion, agentic decision logic, exception routing, and portfolio-wide observability for technical decision-makers.
This workflow automates the real-time sequencing of chillers, pumps, and cooling towers based on building occupancy, weather forecasts, and real-time energy pricing. It reduces peak demand charges and extends equipment life by 15-20% through AI-driven load forecasting and control logic. The page details the integration of BMS points, weather APIs, and reinforcement learning agents within a LangGraph orchestration layer for portfolio-scale deployment.
This automation workflow adjusts HVAC setpoints and airflow for individual building zones by fusing data from occupancy sensors, calendar bookings, and Wi-Fi analytics. It eliminates energy waste in unoccupied areas while maintaining comfort, typically saving 20-30% on zone-level conditioning costs. The architecture combines IoT sensor streams, a rules engine for tenant policies, and direct control over VAV units via BACnet/IP integration.
This workflow automates fresh air intake and exhaust fan speeds based on real-time CO2, VOC, and particulate matter readings to meet ASHRAE 62.1 dynamically. It reduces fan energy use by 25-40% while ensuring air quality compliance in auditoriums, classrooms, and conference centers. The page covers sensor integration, control sequence logic, and the safety overrides required for fail-safe operation in critical environments.
This multi-agent workflow coordinates dimmable LED fixtures and motorized blinds to maintain target lux levels using ambient light sensors and sun position algorithms. It cuts lighting energy consumption by 40-60% in perimeter zones and reduces solar heat gain. The implementation details include DALI or KNX protocol integration, astronomical clock scheduling, and tenant override interfaces via building apps.
This automation workflow uses vehicle detection sensors and license plate recognition to activate lighting and ventilation only in occupied parking zones and aisles. It slashes garage energy costs by up to 70% and extends luminaire life. The page explains the computer vision or radar sensor integration, the safety logic for minimum light levels, and the BMS command layer for staged equipment activation.
This workflow automatically grants and revokes building and floor-level access credentials by syncing with HR systems like Workday or ADP and employee calendars. It eliminates manual badge updates, reduces security tailgating risk, and streamulates move-in/move-out processes. The architecture details the API orchestration between IAM, access control systems (e.g., Lenel, Genetec), and approval workflows for exceptions.
This AI agent monitors access control logs in real-time, using behavioral baselines to flag unusual entry patterns, door-forced-open events, or credential misuse outside business hours. It reduces security response time from hours to minutes and provides auditable incident reports. The page covers the event streaming pipeline, anomaly detection models, and integration with PSIM systems and guard tour software for automated dispatch.
This end-to-end workflow automates visitor registration, host approval, health/NDA compliance checks, and thermal-printed badge issuance upon arrival. It cuts lobby wait times by 80% and improves security log accuracy. Implementation focuses on webhook integration with visitor kiosks, email/SMS notification agents, and direct printing commands to badge systems, with escalation paths for screening failures.
This workflow ingests real-time data from elevator controllers, vibration sensors, and door cycle counters to predict mechanical failures before they cause outages. It reduces downtime by 30% and transforms maintenance from calendar-based to condition-based. The page details the IoT data pipeline, failure prediction models, and automated work order creation in CMMS systems like IBM Maximo or ServiceNow.
This automation system uses a mesh network of wireless moisture sensors to detect water intrusion in real-time, pinpoint the location, and automatically alert facilities teams via SMS and CMMS tickets. It prevents extensive interior damage and reduces leak investigation time from days to minutes. The architecture covers low-power sensor communication, cloud-based alert logic, and integration with building drawings for location mapping.
This multi-agent workflow triages incoming service requests from tenants, BMS alarms, and IoT sensors, creates prioritized work orders, and dispatches them to the appropriate internal team or vendor based on SLA, skill, and location. It cuts mean-time-to-repair by 50% and improves first-time fix rates. The page explains the NLP classification of requests, the dispatch logic, and the two-way sync with vendor portals and technician mobile apps.
This workflow links predictive maintenance alerts for assets like HVAC motors and pump seals with spare parts inventory levels to trigger automatic purchase orders before a failure occurs. It reduces emergency part sourcing costs and equipment downtime. Implementation details include integration between CMMS, ERP procurement modules (e.g., SAP), and supplier APIs, with reorder logic based on lead time and criticality.
This agentic workflow syncs occupancy sensor data, calendar systems (Microsoft 365, Google Workspace), and digital signage to display true room availability and automatically resolve double-bookings by suggesting alternatives. It improves space utilization by 20% and reduces administrative overhead. The page covers the sensor-to-calendar sync logic, the LLM-powered conflict resolution agent, and the notification system for affected users.
This workflow aggregates data from Wi-Fi, cameras, and badge readers to generate real-time and historical heat maps of building occupancy. It automatically adjusts janitorial cleaning schedules and security patrol routes to focus on high-traffic areas, reducing labor costs by 15-25%. The architecture details data anonymization, geospatial analytics, and integration with workforce management and guard tour systems.
This system automatically assigns desks to employees based on team adjacency preferences, historical usage, and real-time bookings, then triggers cleaning work orders after each use. It maximizes flexible seating utilization and ensures health standards. The page explains the optimization algorithm, the mobile app interface for users, and the IoT integration with desk occupancy sensors and cleaning cart tablets.
This workflow collects interval data from hundreds of electrical, water, and gas sub-meters, normalizes it, allocates common area usage, and generates accurate, auditable tenant invoices. It eliminates manual meter reading and billing errors, improving cash flow. Implementation focuses on IoT meter networks, data validation rules, and integration with billing software like Yardi or MRI, including dispute handling workflows.
This workflow controls on-site battery storage and solar PV inverters, deciding when to store, consume, or sell back energy based on live utility rates, building load, and weather forecasts. It maximizes renewable self-consumption and creates a new revenue stream. The architecture covers integrations with DERMS, solar inverters (e.g., SolarEdge), battery management systems, and wholesale market price feeds.
This agentic workflow pulls energy, water, waste, and indoor air quality data from fragmented BMS, IoT, and utility systems across a portfolio, maps it to GRESB and LEED frameworks, and generates draft submission reports. It reduces manual reporting effort by hundreds of hours annually. The page details the data connectors, the LLM-powered framework mapping, and the review/approval gates for compliance teams.
This multi-agent workflow classifies incoming tenant requests via chat, email, or portal using NLP, retrieves relevant lease and service history, and either auto-resolves with instructions, schedules a maintenance ticket, or escalates to a human agent. It improves tenant satisfaction and reduces call center volume by 40%. Implementation covers chatbot integration, knowledge base retrieval, and CRM (e.g., Salesforce) updates.
This workflow automates package logging via carrier APIs or computer vision at package rooms, notifies residents via app, manages pickup via QR code, and handles overflow or perishable items. It eliminates front-desk package management labor. The page details the integration with locker systems (e.g., Luxer One), carrier APIs, resident apps, and the logic for exception handling like missed pickups.
This system analyzes tenant tenure, market rates, and occupancy costs to identify renewal candidates, triggers personalized outreach campaigns, and provides leasing agents with negotiation briefs and alternative space options. It improves retention rates and reduces broker commissions. The architecture integrates CRM, lease administration (e.g., VTS), market data feeds, and email automation platforms.
This workflow automatically detects planned maintenance or unplanned outages from CMMS or BMS, determines affected tenants based on floor/zone, and sends personalized, multi-channel notifications (app, email, SMS) with expected resolution times. It reduces inbound inquiry calls by 80% during incidents. The page covers event detection, tenant mapping logic, and integration with mass notification systems like Everbridge.
This automation workflow schedules periodic drone flights, processes captured imagery with computer vision to detect cracks, blisters, and ponding water, scores roof condition, and generates prioritized repair recommendations and capital plans. It replaces risky manual inspections and improves budget forecasting. Implementation details include flight planning software integration, CV model training, and report generation for asset management platforms.
This workflow aggregates real-time condition data from IoT sensors, maintenance records, and inspection reports to score asset health, forecast end-of-life, and generate optimized multi-year capital replacement plans. It shifts capital spending from reactive to strategic, improving ROI. The page explains the data fusion from CMMS and BIM, the forecasting models, and the integration with financial planning software.
This system automatically identifies equipment failures covered under warranty by matching work order data to asset warranty records, compiles required evidence (serial numbers, failure codes), and submits claims directly to manufacturer portals via API. It recovers thousands in annual repair costs. The architecture details the link between CMMS asset registers, warranty databases, and RPA or API agents for form submission.
This workflow uses protocol gateways and data normalization agents to ingest data from legacy BACnet MS/TP, Modbus, and LonWorks systems, converting it into a unified, cloud-ready data model. It unlocks analytics and automation for older buildings without a full BMS rip-and-replace. The page covers the edge gateway architecture, data point mapping, and the creation of a unified API layer for upstream applications.
This multi-agent system ingests alarms from HVAC, power, fire, and access systems, correlates them by time and location to identify a single root-cause event, and suppresses redundant notifications. It reduces alarm fatigue for operators and speeds incident diagnosis. Implementation details the event correlation engine, the knowledge graph of system dependencies, and the prioritized alerting dashboard for NOC teams.
This workflow establishes a bidirectional sync between a building's digital twin (e.g., in Autodesk Tandem) and live sensor/control data from the BMS, enabling what-if simulations, performance benchmarking, and virtual commissioning. It improves design validation and operational troubleshooting. The page details the real-time data pipeline, the twin update logic, and the use cases for predictive control testing.
This integration workflow creates a unified operational layer by orchestrating data flows and actions between Building Management, Computerized Maintenance, and Integrated Workplace Management Systems. It eliminates silos, providing a single dashboard for energy, maintenance, and space metrics. The architecture focuses on middleware design, event-driven triggers, and role-based data presentation for portfolio managers.
This healthcare-specific workflow automates the control of anteroom and patient room pressurization based on occupancy status and patient infection protocols to contain airborne contaminants. It ensures continuous compliance with ASHRAE 170, reducing infection risk. The page details the integration with nurse call systems, the critical control sequences, and the fail-safe alarms required for life-safety environments.
This workflow continuously monitors and adjusts fume hood sash positions and exhaust fan speeds to maintain safe face velocity, ensuring researcher safety and reducing lab HVAC energy use by up to 50%. It automates alarm generation and emergency protocols for velocity breaches. Implementation covers velocity sensor integration, VAV control logic, and alerts routed to lab managers and facility engineers.
This workflow uses people-counting cameras at entrances to dynamically adjust in-store lighting scenes and HVAC setpoints, creating an inviting ambiance during peak hours and saving energy during lulls. It improves customer experience and reduces operational costs. The architecture covers the CV analytics pipeline, the lighting control system (e.g., Lutron) integration, and the rules for gradual setpoint changes.
This system predicts guest arrival times by analyzing flight data, booking patterns, and mobile app check-ins, then automatically triggers HVAC pre-conditioning, lighting scenes, and digital welcome messages in the assigned room. It enhances guest satisfaction and reduces energy waste from conditioning empty rooms. The page details the predictive model, the integration with PMS (e.g., Opera) and in-room control systems.
This financial workflow ingests invoices for property taxes, insurance, and maintenance, allocates costs to tenants based on lease terms and prorated square footage, and generates detailed CAM reconciliation statements. It eliminates months of manual accounting work and reduces tenant disputes. Implementation focuses on OCR/LLM for invoice data extraction, lease abstraction data, and integration with accounting software like MRI or Yardi.
This AP workflow captures vendor invoices via email or portal, extracts line items using LLMs, matches them to POs and work orders, routes for approval, and schedules payments in the ERP. It reduces processing cost per invoice by 70% and improves early-payment discounts. The page details the document AI pipeline, the 3-way matching logic, and the integration with systems like Sage Intacct or SAP.
This safety workflow plans fire drills according to jurisdictional codes and tenant schedules, sends pre-notifications, triggers alarm systems, monitors evacuation via access control egress events, and generates compliance reports automatically. It ensures consistent, documented safety training. The architecture integrates with fire alarm panels (e.g., Siemens, Notifier), mass notification systems, and compliance databases.
This workflow enables employees to badge in via smartphone Bluetooth, while simultaneously checking their health screening status from a connected wellness app before unlocking turnstiles or elevators. It streamulates safe access and eliminates manual screening lines. The page details the mobile app development, the integration between access control and health survey platforms, and the privacy-preserving data flow.
This system monitors flow meters and pressure sensors across a building's water system, establishes baselines, detects anomalies indicative of leaks, and can automatically trigger zone shut-off valves to prevent major damage. It reduces water waste and mitigates flood risk. Implementation covers IoT sensor networks, anomaly detection algorithms, and integration with smart valve controllers and maintenance systems.
This workflow manages a network of EV chargers, dynamically allocating available power based on building-wide electricity demand, real-time pricing, and driver priority settings to avoid peak demand spikes. It enables EV infrastructure expansion without costly panel upgrades. The page details the OCPP protocol integration with charger networks, the load management algorithm, and the driver notification system for charging delays.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
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