AI for Maintenance & Operations

Machine learning triages building alarms, prioritizes the events that affect safety, uptime, or comfort, and converts validated alarms into work orders inside a facility's existing CMMS.

JoyAI, HappyCo's custom-trained AI companion, runs centralized maintenance for multifamily operators: it enriches and categorizes work orders, matches technicians by skills and location, and powers 24/7 resident communications.

JenZen, Zentility's automated energy assistant, continuously scans energy markets, aggregates portfolio data, and recommends procurement and rate moves for commercial real estate teams.

Aiden, Lessen's AI maintenance product suite, runs the work order lifecycle from intake to dispatch to invoicing across residential and commercial properties.

MAX, Mezo's AI maintenance assistant, intakes resident requests by phone, SMS, and chat, then diagnoses the issue and produces a work order enriched with recommended repairs, parts, and tools.

SMRT IQ adds a conversational AI layer over live IoT device data, so property teams ask plain-language questions and get real-time answers without analytics training.

Computer vision sensors detect workplace occupancy on-device, and a generative AI assistant turns that occupancy data into space optimization recommendations through a natural language interface.

Autonomous AI optimizes commercial HVAC: deep learning neural networks forecast each zone's indoor temperature several hours ahead, then reinforcement learning sends live setpoint commands to the equipment without human input.

Automates multifamily utility billing with agentic AI and anomaly detection, flagging billing errors and powering real-time resident support.

Agentic AI ingests and normalizes data from BMS, meters, and sensors to build digital twins of building systems, then ranks energy optimization opportunities by economic impact and automates the control changes that capture them.

Autonomous building control runs on the edge through PassiveLogic's Hive platform, which uses physics-based 'Quantum' digital twins and a differentiable AI compiler to optimize HVAC and energy in real time.

Automates rental cleaning and maintenance from request to completion.

Breezeway runs AI across property care and guest messaging, drafting suggested replies from property and reservation data and auto-generating cleaning, maintenance, and turnover tasks from reservation triggers.

Enertiv runs machine learning models on equipment sensor data to flag faults before they cause failures, turning building telemetry into predictive maintenance and CapEx planning for commercial real estate operators.

Runwise runs building heating, cooling, water, and gas systems autonomously, pairing a wireless sensor network with machine learning and forward-looking weather forecasts to operate equipment more efficiently than manual or timer-based controls.

Brickwise runs an AI property manager called Alice that handles tenant calls, texts, emails, and WhatsApp around the clock. When a tenant reports an issue, Alice diagnoses severity against the tenancy agreement and local regulations, sources approved contractors for quotes, books the repair, and follows up, then logs everything to the manager's CRM.

ConeLabs converts field imagery from smartphones, cameras, or drones into inspection-grade 3D photogrammetric models, then runs AI defect detection to find and categorize issues like cracks, water infiltration, poor insulation, and weather damage. It quantifies the location and severity of each defect and generates structured inspection reports in one workflow.

Hank plugs into a building's existing automation system and builds a cloud digital twin, then uses machine learning to make continuous micro-adjustments to HVAC and equipment in real time. It autonomously controls building systems to cut energy use while holding occupant comfort and air quality.

Paraspot uses computer vision to run remote, self-guided property inspections from a tenant's phone. The AI validates scan coverage in real time, detects damage like cracks, stains, and missing items, and generates time-stamped, room-categorized reports that support deposit decisions and faster unit turns.