Predict and Prevent Impending
Equipment Failures with Confidence
Award-winning Enterprise Predictive Maintenance Software solutions for asset-intensive industries that helps reduce major component failures, improve the reliability of assets and safely boost production while decreasing maintenance costs.
Control Your Assets. Control Your Profits.
The profitability of your operation is significantly impacted by the availability and health of essential physical assets.
DINGO, the global leader in Predictive Maintenance, unites people and award-winning technology to provide actionable intelligence to asset-intensive industries.
- Optimize planning
- Minimize downtime and repair costs
- Create a safer workplace
- Maximize asset health
- Deliver superior financial results
Trakka Software
Asset Health Management App
Condition Intelligence
Savings Calculator
246
Operations use DINGO’s predictive analytics software
6
Serving clients on 6 continents
$13.5 Billion
Of equipment under management
$1 Billion
Saved in maintenance and replacement costs
We Keep Your Assets Healthy and Operations Running Smoothly

Equipment failure does not happen on a schedule. Without an effective asset maintenance program that lets you predict and stop costly breakdowns before they occur, you risk facing:
- Unmet production goals,
- Unplanned downtime,
- Avoidable safety incidents,
- Unnecessary maintenance and capital expenditures,
- Lower profitability.
Predict Today. Perform Tomorrow.
Optimize your maintenance department today and build a successful strategy for tomorrow by implementing DINGO’s industry-leading Asset Health program.
Trakka® – our award-winning predictive analytics and workflow management tool, collects, analyzes and distills equipment data to the exact actions that drive results.
Stop looking for issues and start solving them with Trakka®.
Sustainable Fleet Maintenance Solution Built for Every Level of Your Organization

Corporate Management
- View the state of your fleet’s health in real-time.
- Optimize return on your assets while measuring the improved financial results.
- Drive maintenance costs down to reduce AISC, improving site and enterprise profitability.
- Upskill your workforce and scale disciplined maintenance processes.
- Increase your teams’ capacity and build collaboration among teams and sites.

General Management
- Maximize the availability of key assets to achieve site production goals.
- Integrate with your existing systems and access all data in one place.
- Make decisions faster while empowering accountability.
- Establish proven processes that can be scaled to various asset groups at your site and other operations.

Maintenance & Reliability
- Quickly achieve Condition-Based Maintenance and reduce unnecessary work orders.
- Leverage DINGO’s Data Science team to accurately predict time until component failure.
- Seamlessly integrate into maintenance workflows with recommendations flowing directly into your ERP and CMMS.
- Automatically track KPIs to demonstrate the value of your team’s predictive maintenance program.
Industries We Serve
Join the leading companies in asset-intensive industries in optimizing asset performance
and achieving operational excellence.
Defence
Shorten diagnostic time and prioritize repairs to support sustained readiness and ensure the safety of your troops.
Wind
Prevent unplanned downtime and costly damage to turbine components.
Oil & Gas
Proactively identify impending issues on critical components to prioritize and plan maintenance.
Rail
Avoid in-service engine failures and plan for long-term component management.
Mining
Keep your fleet availability at target levels while improving operational efficiency.
Quickly bring components back into normal operating range
Condition-based asset management is key to keeping our fleet availability at target levels while ensuring we are running at the lowest operating cost per hour.
Maintenance Manager at a large Canadian copper mine
Accelerate the adoption of consistent maintenance strategies
By utilizing the Dingo Trakka® system , our company will streamline and standardize its predictive maintenance processes, tools and services worldwide.
Senior Director Operations Support Hubs for a leading gold mining company
DINGO’s Enterprise-Level Asset Health
Solution Saved One Major Gold Miner
Over $83 Million over 15+ years.
![DINGO supports mining in Latin America [GBR Chile Mining Report 2022]](https://dingo.com/wp-content/uploads/2021/06/dingo-company-news-press.jpg)
![DINGO supports mining in Latin America [GBR Chile Mining Report 2022]](https://dingo.com/wp-content/uploads/2021/06/dingo-company-news-press.jpg)
![DINGO supports mining in Latin America [GBR Chile Mining Report 2022]](https://dingo.com/wp-content/uploads/2021/06/dingo-company-news-press.jpg)
DINGO supports mining in Latin America [GBR Chile Mining Report 2022]
DINGO has a great and growing team that supports mining operations in South America. "Having local capabilities with employees that speak Spanish and understand the different cultures in the region is important for business development and to ensure operations run...
![DINGO supports mining in Latin America [GBR Chile Mining Report 2022]](https://dingo.com/wp-content/uploads/2021/06/dingo-company-news-press.jpg)
![DINGO supports mining in Latin America [GBR Chile Mining Report 2022]](https://dingo.com/wp-content/uploads/2021/06/dingo-company-news-press.jpg)
![DINGO supports mining in Latin America [GBR Chile Mining Report 2022]](https://dingo.com/wp-content/uploads/2021/06/dingo-company-news-press.jpg)
DINGO supports mining in Latin America [GBR Chile Mining Report 2022]
DINGO has a great and growing team that supports mining operations in South America. "Having local capabilities with employees that speak Spanish and understand the different cultures in the region is important for business development and to ensure operations run...


Trakka 4.8.8 Release Notes
Trakka 4.8.8 has now been released, see attached release notes for more info of what's new in the release. Trakka Release Notes 4.8.8 - English Trakka Release Notes 4.8.8 - Español