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What is Zapium?

Zapium is a next-generation maintenance management ecosystem built to help businesses streamline operations, reduce downtime, and achieve higher reliability across their asset portfolios. It combines CMMS, facility maintenance management, and field service tools into a cohesive platform that automates everything from work orders and scheduling to inspections, routing, and asset tracking. Using predictive and preventive maintenance capabilities, Zapium equips organizations to prevent breakdowns by monitoring asset conditions through IoT sensors and real-time health insights. Field technicians benefit from smart mobile collaboration features, including offline mode, auto-sync, embedded checklists, digital forms, and geo-tagged time entries that increase accountability and transparency. Zapium’s AI-powered knowledge base helps teams instantly diagnose recurring issues using historical maintenance data, reducing resolution time and improving first-time fix rates. Modern approval workflows, vendor management modules, purchase order tools, and RFQ management ensure that every maintenance activity is consistent, auditable, and efficient. Analytics dashboards offer leaders a complete view of maintenance KPIs, cost trends, asset performance, and workforce utilization. The platform is tailored for dozens of industries—such as construction, mining, hotels, banks, pharma manufacturing, landscaping, fleet maintenance, and energy—making it adaptable to unique operational needs. With strong security controls, customizability, and enterprise-level scalability, Zapium is engineered to evolve alongside growing businesses. Whether improving technician productivity or optimizing long-term asset reliability, Zapium delivers measurable impact across the entire maintenance lifecycle.

What is PreCognize?

In a highly interconnected process industry characterized by a lack of historical data, the challenge of unpredictable failures remains ever-present. Our all-encompassing monitoring solution effectively detects quality issues, equipment breakdowns, operational deviations, and unusual process activities. Instead of wading through a sea of false alarms, we refine this to provide no more than five significant alerts each day. This system enables advanced warnings of potential failures, with notifications issued anywhere from a week to just 24 hours in advance, thereby preventing unexpected interruptions during off-peak hours. By focusing on proactive and scheduled maintenance, we not only boost operational efficiency but also significantly lower costs. The distinct requirements of industrial assets call for a creative strategy; we expertly combine your team's knowledge with cutting-edge machine learning technologies to establish a customized predictive monitoring framework. Using your current sensors and data, the setup is quick; within two weeks, a process engineer can map out the plant's structure and functions, after which the software becomes fully functional, laying the groundwork for enhanced reliability and performance. This swift implementation guarantees that your operations can rapidly reap the rewards of improved monitoring capabilities, ultimately fostering a more resilient industrial environment.

Media

Media

Integrations Supported

PI Vision
dataPARC Historian

Integrations Supported

PI Vision
dataPARC Historian

API Availability

Has API

API Availability

Has API

Pricing Information

$10/user/month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Zapium

Date Founded

2018

Company Location

United States

Company Website

www.zapium.com

Company Facts

Organization Name

PreCognize

Company Location

United States

Company Website

www.precog.co

Categories and Features

CMMS

Asset Tracking
Calibration Management
Inventory Control
Key & Lock Management
Mobile Access
Preventive Maintenance
Purchasing
Scheduling
Service History Tracking
Technician Management
Work Order Management

Field Service Management

Billing & Invoicing
Contact Database
Contract Management
Customer Database
Dispatch Management
Electronic Signature
Inventory Management
Mobile Access
Payment Collection in the Field
Quotes / Estimates
Routing
Scheduling
Service History Tracking
Time Clock
Work Order Management

Maintenance Management

Asset Tracking
Billing & Invoicing
Calibration Management
Dispatch Management
Inventory Control
Inventory Management
Key & Lock Management
Mobile Access
Planning Calendar
Predictive Maintenance
Preventive Maintenance
Purchasing
Scheduling
Service History Tracking
Technician Management
Work Order Management

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management

Work Order

Contract Management
Customer Database
Dispatch Management
Inventory Control
Job Management
Preventive Maintenance
Quotes / Estimates
Recurring Appointments
Routing
Scheduling
Task Management

Categories and Features

Maintenance Management

Asset Tracking
Billing & Invoicing
Calibration Management
Dispatch Management
Inventory Control
Inventory Management
Key & Lock Management
Mobile Access
Planning Calendar
Predictive Maintenance
Preventive Maintenance
Purchasing
Scheduling
Service History Tracking
Technician Management
Work Order Management

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management

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