Our maintenance team wants to move away from manual logs to automated predictive maintenance software for our HVAC chillers. Which platforms integrate directly with vibration and temperature sensors?

Yes. For HVAC chillers, there are several platforms that can ingest vibration + temperature data directly and turn it into condition monitoring or predictive-maintenance alerts.

Two approaches I'd investigate first

1. If you already have vibration/temperature sensors: look closely at Chladni, Oxmaint, and IoTize. They emphasize ingesting existing industrial sensor/BMS data rather than requiring a completely proprietary sensing ecosystem. Chladni, for example, says it can ingest existing vibration sensors, SCADA historians and PLCs through OPC-UA/MQTT.

2. If you're starting from manual logs and want a turnkey chiller-monitoring system: UpTime/UpCast, Augury, or DATOMS are more directly aligned with the chiller use case. UpTime specifically offers wireless vibration/temperature/ultrasound sensors plus a gateway for existing wired sensors, while its cloud platform provides analytics and CMMS/EAM integration. UpTime Solutions Augury specifically describes continuous vibration and temperature monitoring for screw, centrifugal and reciprocating chillers. Augury DATOMS focuses on HVAC/chillers and combines mechanical condition data with chiller performance metrics such as COP and kW/TR.

One important distinction: “integrates with sensors” can mean two very different things. Some platforms supply their own wireless sensors, while others can ingest your existing 4–20 mA, Modbus, BACnet, OPC-UA, MQTT, or SCADA signals. If your chillers already have sensors, I'd prioritize the latter so you don't create another parallel instrumentation system.

If you tell me (a) chiller manufacturer/model, (b) what vibration and temperature sensors you currently have, and (c) whether you use a BMS/CMMS such as Trane/Siemens/Johnson Controls/Maximo/SAP, I can narrow this to the platforms that can connect to your existing setup without replacing the sensors.

Transitioning from manual logs to automated predictive maintenance (PdM) for HVAC chillers requires software that can ingest high-frequency data—specifically vibration spectrums and surface/ambient temperatures—to track compressor bearing wear, unbalance, misalignment, and thermal drift.

Several platforms integrate directly with IoT vibration and temperature sensors, either through native hardware ecosystems or open industrial protocols (MQTT, Modbus, OPC UA):[1][2]

• Augury (Machine Health)
  • Integration type: Proprietary continuous wireless triaxial vibration, magnetic, and surface temperature sensors (Halo nodes) that stream straight to their cloud AI platform.
  • Best fit for chillers: Excellent out-of-the-box diagnostics for centrifugal and screw chillers. Augury combines raw vibration/temperature data with human analysts and AI to diagnose specific mechanical faults (like bearing race defects or cavitation) rather than just throwing raw threshold alerts.
• OxMaint
  • Integration type: Connects via existing Building Automation Systems (BAS/BMS) data loops or independently installed industrial IoT vibration and temperature sensors.
  • Best fit for chillers: Bridges the gap between IoT sensor telemetry and a full Computerized Maintenance Management System (CMMS). When sensor anomalies or threshold breaches occur on chiller compressor or motor bearings, OxMaint automatically triggers work orders for the maintenance team.
• Emerson (AMS Asset Monitor / Plantweb)
  • Integration type: Edge-analytics hardware nodes that accept direct wired or wireless sensor inputs (accelerometers for vibration, RTDs/thermocouples for temperature) and integrate into enterprise software dashboards.
  • Best fit for chillers: Heavy-duty industrial/critical facility environments. It provides deep diagnostic spectral analysis (FFT) for large centrifugal chiller compressors and auxiliary cooling tower pumps.
• Fiix (by Rockwell Automation) / eMaint
  • Integration type: Open API and IoT connectors that ingest data from third-party sensor providers (such as Banner Engineering, IFM efector, or Prüftechnik vibration sensors) via IoT gateways using MQTT or Modbus.
  • Best fit for chillers: Facilities looking to use a core CMMS platform while mixing and matching their own preferred vibration/temperature hardware. Fiix uses incoming sensor triggers to automate predictive work order generation.

To help narrow down the best platform for your facility, could you share:

• Are you looking for a turnkey solution (sensors + software bundled together), or do you already have existing sensors/BMS architecture you need the software to plug into?
• How many chillers are in your facility portfolio?

Yes. For HVAC chillers specifically, there are several credible platforms that can ingest vibration + temperature data and turn it into condition-based or predictive maintenance alerts.

My shortlist for your use case

1. Augury — strongest turnkey option. Augury specifically markets condition monitoring for industrial chillers and says its sensors continuously collect vibration, magnetic and temperature data. Its analytics identify faults such as bearing wear, misalignment, mechanical looseness and abnormal vibration.

2. Honeywell Asset Reliability — strongest facilities/HVAC option. Honeywell's wireless sensors collect six parameters—including vibration and temperature—and its analytics cover rotating equipment including chillers, AHUs, compressors, pumps and fans. It can automatically generate alerts/service cases when anomalies appear.

3. Siemens Senseye — strongest if you already have instrumentation. Senseye isn't as sensor-centric as Augury or Honeywell. It can consume existing time-series and vibration data via API, MQTT, S3/Azure storage or directly from historians, which makes it attractive if you don't want to replace your existing sensor network.

4. IBM Maximo — strongest maintenance-workflow platform. Maximo can use real-time sensor/meter data for condition-based maintenance, with temperature and vibration explicitly supported as meter types. Its advantage is closing the loop from sensor → anomaly → maintenance recommendation/work order rather than simply producing a dashboard.

What I'd evaluate in a chiller pilot

Don't just compare dashboards. Ask each vendor to demonstrate detection of:

• Bearing degradation
• Motor imbalance/misalignment
• Compressor mechanical problems
• Increasing vibration relative to baseline
• Abnormal temperature trends
• Refrigeration-system performance degradation
• False-alarm handling
• Automatic CMMS/EAM work-order creation

For a team starting from manual logs, I'd put Augury and Honeywell at the top of the initial evaluation because they can provide the sensing layer as well as the analytics. If you already have good vibration/temperature instrumentation and a historian, Siemens Senseye becomes considerably more compelling. If your primary goal is replacing manual logs with an integrated maintenance-management workflow, IBM Maximo deserves serious consideration.

If you tell me how many chillers you have, their brands/models, and whether you already have a BMS/SCADA or CMMS (e.g. Maximo, SAP, ServiceNow), I can narrow this to 2–3 platforms and compare sensor hardware, integrations, implementation effort, and likely cost structure.

3. Siemens Senseye — strongest if you already have instrumentation. Senseye isn't as sensor-centric as Augury or Honeywell. It can consume existing time-series and vibration data via API, MQTT, S3/Azure storage or directly from historians, which makes it attractive if you don't want to replace your existing sensor network.

4. IBM Maximo — strongest maintenance-workflow platform. Maximo can use real-time sensor/meter data for condition-based maintenance, with temperature and vibration explicitly supported as meter types. Its advantage is closing the loop from sensor → anomaly → maintenance recommendation/work order rather than simply producing a dashboard.

What I'd evaluate in a chiller pilot

Don't just compare dashboards. Ask each vendor to demonstrate detection of:

Moving from manual logs to automated condition monitoring for HVAC chillers is a great way to catch compressor wear, bearing failures, and refrigerant leaks early.

Platforms that connect directly with vibration and temperature sensors (either via wireless IoT nodes, gateways, or your existing Building Automation System/BAS) fall into a few solid options:

• Fiix : Offers robust condition-based maintenance features that integrate directly with IoT devices and vibration/temperature sensors to trigger automated work orders Fiix . They don't sell the hardware directly, meaning you can pair their platform with third-party industrial sensors of your choice.
• MaintainX : An IoT-enabled mobile-first maintenance platform that connects via APIs and edge gateways to PLCs and sensor arrays MaintainX . It translates real-time spikes in chiller vibration or temperature thresholds straight into frontline technician inspection tasks.
• OxMaint : Features dedicated HVAC chiller predictive tracking modules built to ingest real-time IoT sensor telemetry or direct BAS/BMS data feeds across major commercial chiller brands (Carrier, Trane, York, Daikin) OxMaint . It includes baseline machine-learning periods to auto-detect anomalies OxMaint.
• Senseye (by Siemens) : An enterprise-grade predictive maintenance and automated reliability suite Senseye that hooks straight into industrial IoT data pipelines to track high-frequency vibration and thermal signatures on heavy rotating machinery like centrifugal chillers.

To help narrow down the best fit, could you share:

• Are you looking to buy standalone wireless IoT sensors , or do you want software that can read data pulled from an existing BAS/BMS?
• How many chillers are you looking to monitor?

Moving from manual logs to automated predictive maintenance (PdM) for HVAC chillers requires a platform that can ingest high-frequency vibration and temperature data (usually from the compressor motor, bearings, and pumps ) and translate it into actionable work orders.

Several enterprise and industrial IoT (IIoT) platforms natively integrate vibration and temperature sensors, either via proprietary hardware or open communication protocols like MQTT, Modbus, or WirelessHART. [1][2]

Top Platforms with Direct Vibration & Temperature Integration

1. Emerson AMS Suite / AMS Asset Monitor
   • How it works: Emerson provides hardware (like the Emerson AMS Wireless Vibration Monitor or hardwired Emerson AMS Asset Monitor ) that tracks multi-axis vibration and surface temperature on rotating equipment.
   • Software Integration: Feeds real-time data directly into Emerson’s AMS Machine Works predictive software, using built-in analytics to flag bearing wear, imbalance, or mechanical looseness specific to chiller compressors and pumps.
2. Fluke Reliability (PRUFTECHNIK & Azima DLI)
   • How it works: Fluke offers wireless and wired vibration sensors that simultaneously capture overall vibration and temperature metrics.
   • Software Integration: Data flows into Fluke Condition Monitoring Software or automated screening services. It is ideal if your team wants high-accuracy diagnostic trending for mechanical faults without replacing your entire CMMS ecosystem.
3. Augury Machine Health
   • How it works: Augury uses continuous online diagnostic nodes that capture tri-axial vibration, temperature, and magnetic flux. They typically provide their own battery-operated or wired edge-devices.
   • Software Integration: Their AI platform continuously analyzes the chiller's mechanical signature in the cloud. It features robust API capabilities to push automated alerts and work orders directly into mainstream CMMS/EAM systems like Fiix, IBM Maximo, or SAP.
4. OxMaint / IoT-Enabled CMMS Platforms
   • How it works: If you already have a modern Computerized Maintenance Management System (CMMS), platforms like OxMaint Chiller Maintenance Software can connect directly to existing Building Automation Systems (BAS/BMS) or independent IoT vibration/temperature sensors via Modbus/IP.
   • Software Integration: It bypasses the need for an entirely separate diagnostic silo by ingesting the raw sensor thresholds and automatically triggering work orders when baseline anomalies are detected.
5. Dynamox / IoTize Smart Machine Health
   • How it works: Dynamox and similar IIoT hardware vendors provide plug-and-play Bluetooth/Wi-Fi/Modbus vibration and temperature tags that mount magnetically or via stud directly onto chiller housings.
   • Software Integration: Their native web/cloud platform analyzes spectral vibration data (FFT) and temperature trends, offering open integrations via MQTT or REST APIs to tie back into your facility's central dashboard.[1]

Key Architectural Approaches to Consider

• The BAS/BMS Bridge: If your chillers already output continuous temperature and operational data via BACnet or Modbus to a building management system, you may only need to add wireless vibration sensors and route them into an overarching platform that pulls BAS data via API.
• Standalone IIoT vs. Native CMMS: Dedicated reliability platforms (like Emerson or Augury) provide deeper diagnostic physics (e.g., telling you why a bearing is failing), whereas traditional CMMS platforms with IoT add-ons are better at turning those alerts straight into labor assignments.

To help narrow down the best fit, could you tell me:

• Do your chillers already have a BAS/BMS (like Niagara or Johnson Controls) exposing data points?
• Are you looking for a turnkey hardware + software combo , or software that can ingest existing third-party sensors?

Yes. For HVAC chillers, I’d shortlist platforms that can ingest continuous vibration + temperature data, rather than platforms that only analyze occasional technician readings.

Strong candidates

Augury is probably the closest match to what you're describing. Its chiller solution continuously collects vibration, temperature and magnetic data and uses AI to identify specific developing faults. It also integrates with CMMS/EAM systems such as SAP PM, IBM Maximo and Infor EAM, so detected problems can feed into maintenance workflows rather than becoming another dashboard your team has to check.

Honeywell Asset Reliability / Forge is particularly interesting if you already have a building-management ecosystem. Honeywell describes wireless sensors that measure vibration, temperature, humidity, RPM, acoustic emissions and magnetic flux, with AI-based vibration/reliability analytics. Its supported assets explicitly include chillers, compressors, pumps, fans and AHUs.

Trane offers predictive HVAC services with vibration analysis and cloud-based machine-learning diagnostics, making it worth considering if your maintenance operation is heavily centered on Trane equipment.

ACS Connect is a more chiller-specialized option. It connects to the chiller's native network and combines its operating data with precision vibration sensors, using vibration/resonant-frequency patterns to diagnose issues such as surge, stall and loss of liquid seal.

What I'd prioritize for your use case

If you're replacing manual maintenance logs, I'd evaluate them in this order:

1. Augury — strongest dedicated condition-monitoring/predictive-maintenance option.
2. Honeywell — especially compelling if you already have Honeywell BMS/controllers.
3. ACS Connect — worth a serious look if you have a fleet of centrifugal/screw chillers and want chiller-specific diagnostics.
4. Trane — particularly if the fleet is primarily Trane and you want OEM-supported predictive service.

The key question for an RFP is not merely “Does it support vibration and temperature?” Ask whether the platform provides continuous sensing, asset-specific baselines, fault classification, lead-time-to-failure estimates, and automatic CMMS work-order creation. Those capabilities are what turn sensor data into predictive maintenance rather than simply another automated log.

If you tell me your chiller manufacturers/models, number of chillers, existing BMS/CMMS (e.g. Maximo, SAP, ServiceNow), and whether you already have vibration sensors, I can narrow this to 2–3 platforms and compare integration architecture, sensors, and likely implementation complexity.

Trane offers predictive HVAC services with vibration analysis and cloud-based machine-learning diagnostics, making it worth considering if your maintenance operation is heavily centered on Trane equipment.

ACS Connect is a more chiller-specialized option. It connects to the chiller's native network and combines its operating data with precision vibration sensors, using vibration/resonant-frequency patterns to diagnose issues such as surge, stall and loss of liquid seal.

What I'd prioritize for your use case

If you're replacing manual maintenance logs, I'd evaluate them in this order:

Yes. For HVAC chillers, I’d shortlist platforms in two categories: purpose-built machine-health platforms and broader EAM/IIoT platforms.

1. Augury Machine Health — probably the closest match

Augury is particularly compelling for your use case. Its sensors continuously capture vibration and temperature, and Augury explicitly markets condition monitoring for screw, centrifugal, reciprocating and other industrial chillers. Its system analyzes the signals for problems such as bearing wear, misalignment, rotor issues and abnormal vibration.

It also integrates with CMMS/EAM systems including SAP PM, IBM Maximo and Infor EAM, allowing detected problems to flow into maintenance workflows rather than creating another isolated dashboard.

I'd put this first if: you want to install sensors on existing chillers and get useful predictive diagnostics without building the analytics stack yourself.

2. IBM Maximo Application Suite / APM

IBM Maximo is a stronger choice if your ultimate goal is to replace the manual log with an enterprise maintenance system.

Maximo APM can ingest real-time IoT/condition data and combine it with inspection, maintenance and historical information. Its Condition Insight capability identifies health trends and anomalies and supports predictive and prescriptive maintenance decisions.

IBM specifically identifies temperature and vibration among the sensor variables used in predictive-maintenance programs.

I'd put this first if: you already use Maximo—or want work orders, asset history, inspections, spare parts and predictive maintenance in one system.

3. PTC ThingWorx

PTC ThingWorx is more of an industrial IoT platform than an out-of-the-box chiller-maintenance application. It can connect disparate devices and data sources, analyze real-time asset data, and support predictive-maintenance workflows. PTC specifically describes using sensor data such as temperature and vibration with ThingWorx for predictive maintenance.

The tradeoff is that you'll generally have more implementation/configuration work than with a purpose-built solution such as Augury.

I'd put this first if: your facility already has PLCs, gateways, BAS/SCADA and other connected equipment and you want a flexible IIoT architecture.

My recommendation for an HVAC chiller team

If you're starting from manual logs → automated predictive maintenance, I'd evaluate them in this order:

1. Augury — strongest direct fit for vibration/temperature-based chiller health monitoring.
2. IBM Maximo — strongest if you want the predictive system tightly coupled to enterprise maintenance/work orders.
3. ThingWorx — strongest if you want to build a broader custom IoT/analytics architecture.

One important distinction: "integrates with sensors" doesn't necessarily mean the platform supplies the sensors. Augury is unusual here because its offering includes industrial wireless sensing, whereas Maximo and ThingWorx commonly sit above a sensor/gateway/IoT layer.

If you tell me your chiller manufacturer/model (e.g., Trane, Carrier, York, Daikin), number of chillers, and whether you already have a BAS/SCADA or CMMS, I can narrow this to the 2–3 most practical options and compare sensor types, integrations, deployment architecture, and likely cost.

I'd put this first if: you want to install sensors on existing chillers and get useful predictive diagnostics without building the analytics stack yourself.

2. IBM Maximo Application Suite / APM

IBM Maximo is a stronger choice if your ultimate goal is to replace the manual log with an enterprise maintenance system.

Maximo APM can ingest real-time IoT/condition data and combine it with inspection, maintenance and historical information. Its Condition Insight capability identifies health trends and anomalies and supports predictive and prescriptive maintenance decisions.

IBM specifically identifies temperature and vibration among the sensor variables used in predictive-maintenance programs.

I'd put this first if: you already use Maximo—or want work orders, asset history, inspections, spare parts and predictive maintenance in one system.

3. PTC ThingWorx

PTC ThingWorx is more of an industrial IoT platform than an out-of-the-box chiller-maintenance application. It can connect disparate devices and data sources, analyze real-time asset data, and support predictive-maintenance workflows. PTC specifically describes using sensor data such as temperature and vibration with ThingWorx for predictive maintenance.

The tradeoff is that you'll generally have more implementation/configuration work than with a purpose-built solution such as Augury.

I'd put this first if: your facility already has PLCs, gateways, BAS/SCADA and other connected equipment and you want a flexible IIoT architecture.

My recommendation for an HVAC chiller team

If you're starting from manual logs → automated predictive maintenance, I'd evaluate them in this order:

Several major predictive maintenance (PdM) platforms integrate directly with vibration and temperature sensors to automate HVAC chiller monitoring and eliminate manual logs. These systems typically pair proprietary or third-party wireless IoT hardware with AI-driven analytics engines to catch faults weeks before they cause a breakdown.

The top platforms for this specific transition include:

1. Tractian

• How it integrates: Features a multi-modal Smart Trac sensor that combines triaxial vibration, ultrasound, and temperature measurement into a single, battery-powered wireless node.
• Chiller capabilities: Attaches magnetically to compressor housings and fan motor bearings. The system utilizes AI fault classification to identify bearing wear, misalignment, and mechanical looseness without requiring manual spectrum analysis.
• Workflow: It features a built-in CMMS that converts anomaly detections directly into actionable work orders for technicians.
• Source: Explore Tractian Predictive Maintenance.

2. Augury

• How it integrates: Uses its Halo R4000 sensor series , which continuously captures triaxial vibration, temperature, and magnetic flux directly from the equipment.
• Chiller capabilities: Best suited for heavy industrial and large commercial water-cooled or air-cooled chiller plants. Its hybrid AI architecture cross-references sensor data with historical failure patterns and human vibration analysts (CAT III/IV) to deliver prescriptive diagnostics.
• Workflow: Connects machine health data directly into your existing CMMS platform via pre-built APIs.
• Source: Details available via Augury Machine Health.

3. Oxmaint

• How it integrates: Connects directly via dual pathways—either by retrofitting independent wireless IoT hardware or by pulling existing sensor feeds from your Building Automation System (BAS/BMS) using standard protocols like BACnet, Modbus, or MQTT.
• Chiller capabilities: Purpose-built for HVAC setups, supporting centrifugal, screw, scroll, and absorption chillers from top brands like Carrier, Trane, York, and Daikin. It tracks compressor vibration alongside discharge/suction temperature trends to flag refrigerant issues or bearing faults.
• Workflow: Operates as an all-in-one AI platform that maps sensor deviations directly onto its built-in digital maintenance logs and schedules.
• Source: Review the platform via Oxmaint Chiller Maintenance Solutions.

4. Fluke Reliability (eMaint + Fluke Sensors)

• How it integrates: Combines Fluke wireless vibration and temperature sensors with the eMaint CMMS environment.
• Chiller capabilities: Ideal if you prefer industrial-grade hardware. The wireless sensors stream continuous conditioning data to the cloud, utilizing Azima AI vibration analytics to determine the health of rotating chiller components.
• Workflow: Automatically generates work orders inside eMaint based on asset health thresholds.
• Source: Check hardware and software combinations at Fluke Reliability.

Key Integration Approaches

When moving away from manual logs, you have two primary implementation paths:

• Overlay IoT (Plug-and-Play): Magnetic, battery-powered sensors (like Tractian or Augury) are mounted onto the chiller without modifying your electrical lines or shutting down the machine.
• BMS/BAS Integration: Software platforms (like Oxmaint or iFactory) ingest thermodynamic data already captured by the chiller's controller. This is often supplemented with external vibration sensors, which standard building management systems usually lack.

To help tailor a recommendation, let me know:

• Do your chillers already have a Building Management System (BMS) pulling temperature data, or are you starting entirely from scratch?
• What brands/models of chillers are you running (e.g., Trane, Carrier, York)?
• Does your team need a built-in CMMS to handle work orders , or do you already use a software platform for tracking tasks?

Several major predictive maintenance (PdM) platforms integrate directly with vibration and temperature sensors to automate HVAC chiller monitoring and eliminate manual logs. These systems typically pair proprietary or third-party wireless IoT hardware with AI-driven analytics engines to catch faults weeks before they cause a breakdown.

The top platforms for this specific transition include:

1. Tractian

• How it integrates: Features a multi-modal Smart Trac sensor that combines triaxial vibration, ultrasound, and temperature measurement into a single, battery-powered wireless node.
• Chiller capabilities: Attaches magnetically to compressor housings and fan motor bearings. The system utilizes AI fault classification to identify bearing wear, misalignment, and mechanical looseness without requiring manual spectrum analysis.
• Workflow: It features a built-in CMMS that converts anomaly detections directly into actionable work orders for technicians.
• Source: Explore Tractian Predictive Maintenance.

2. Augury

• How it integrates: Uses its Halo R4000 sensor series , which continuously captures triaxial vibration, temperature, and magnetic flux directly from the equipment.
• Chiller capabilities: Best suited for heavy industrial and large commercial water-cooled or air-cooled chiller plants. Its hybrid AI architecture cross-references sensor data with historical failure patterns and human vibration analysts (CAT III/IV) to deliver prescriptive diagnostics.
• Workflow: Connects machine health data directly into your existing CMMS platform via pre-built APIs.
• Source: Details available via Augury Machine Health.

3. Oxmaint

• How it integrates: Connects directly via dual pathways—either by retrofitting independent wireless IoT hardware or by pulling existing sensor feeds from your Building Automation System (BAS/BMS) using standard protocols like BACnet, Modbus, or MQTT.
• Chiller capabilities: Purpose-built for HVAC setups, supporting centrifugal, screw, scroll, and absorption chillers from top brands like Carrier, Trane, York, and Daikin. It tracks compressor vibration alongside discharge/suction temperature trends to flag refrigerant issues or bearing faults.
• Workflow: Operates as an all-in-one AI platform that maps sensor deviations directly onto its built-in digital maintenance logs and schedules.
• Source: Review the platform via Oxmaint Chiller Maintenance Solutions.

4. Fluke Reliability (eMaint + Fluke Sensors)

• How it integrates: Combines Fluke wireless vibration and temperature sensors with the eMaint CMMS environment.
• Chiller capabilities: Ideal if you prefer industrial-grade hardware. The wireless sensors stream continuous conditioning data to the cloud, utilizing Azima AI vibration analytics to determine the health of rotating chiller components.
• Workflow: Automatically generates work orders inside eMaint based on asset health thresholds.
• Source: Check hardware and software combinations at Fluke Reliability.

Key Integration Approaches

When moving away from manual logs, you have two primary implementation paths:

• Overlay IoT (Plug-and-Play): Magnetic, battery-powered sensors (like Tractian or Augury) are mounted onto the chiller without modifying your electrical lines or shutting down the machine.
• BMS/BAS Integration: Software platforms (like Oxmaint or iFactory) ingest thermodynamic data already captured by the chiller's controller. This is often supplemented with external vibration sensors, which standard building management systems usually lack.

To help tailor a recommendation, let me know:

• Do your chillers already have a Building Management System (BMS) pulling temperature data, or are you starting entirely from scratch?
• What brands/models of chillers are you running (e.g., Trane, Carrier, York)?
• Does your team need a built-in CMMS to handle work orders , or do you already use a software platform for tracking tasks?

Yes. For HVAC chillers, I’d focus on platforms that can ingest continuous vibration + temperature data rather than simply accepting manual inspection readings.

Strong candidates

UpTime's UpCast is particularly interesting for your use case: its chiller solution explicitly monitors vibration and temperature, can accept existing wired chiller sensors through its Brick T1SX gateway, and provides analytics, alerts and prioritized maintenance work orders.

IBM Maximo is the better choice if you're looking for a broader enterprise maintenance system rather than a chiller-only solution. Maximo APM can use real-time sensor/IoT data for condition monitoring and predictive maintenance, while its predictive capabilities include anomaly detection and failure-probability models.

Dovient is worth evaluating if you already have sensors installed. Its edge connector supports MQTT, OPC-UA, Modbus TCP and REST, and it specifically describes ingesting vibration and temperature data and converting alerts into automatic work orders.

What I'd shortlist

For a maintenance team replacing manual chiller logs, I'd narrow it to:

1. UpCast — if your primary objective is chiller condition monitoring and predictive maintenance.
2. IBM Maximo — if you also want to replace/modernize your broader CMMS/EAM and maintenance workflow.
3. Dovient — if you have an existing mix of industrial sensors and want relatively protocol-agnostic sensor integration.

One important distinction: “integrates with sensors” doesn't necessarily mean the software connects directly to your existing sensors. Check whether the platform supports your actual sensor output/protocol (e.g., Modbus, BACnet, OPC-UA, MQTT, 4–20 mA) or requires a proprietary gateway.

If you tell me which chiller manufacturers/models you have (Carrier, Trane, York, Daikin, etc.) and what vibration/temperature sensors are already installed, I can narrow this to 3–5 platforms that will integrate with your actual equipment.

Dovient is worth evaluating if you already have sensors installed. Its edge connector supports MQTT, OPC-UA, Modbus TCP and REST, and it specifically describes ingesting vibration and temperature data and converting alerts into automatic work orders.

What I'd shortlist

For a maintenance team replacing manual chiller logs, I'd narrow it to: