A company in "Predictive Maintenance Software" develops digital tools or software that help industries predict and address potential equipment failures before they occur. The software uses machine learning and artificial intelligence algorithms to analyze equipment data, identify patterns that may signal upcoming problems, and alert managers. This helps businesses reduce downtime, avoid expensive repair costs, increase operational efficiency, and prolong the lifespan of machinery.

Selecting a predictive maintenance software provider involves a comprehensive process which looks at various factors such as the nature of your business, your budget, integration process, available features, level of support, and feedback from their past and current users.   Here are steps you can take to select an appropriate Predictive Maintenance vendor:  

1. Define Your Goals: Write down exactly what you hope to achieve with the tool. This will include curbing carbon emissions, energy usage etc.  

2. Research: Look for different vendors who provide predictive maintenance software. Research about their reputation, features provided by them, their market presence etc. Consider solutions that are well-adapted to your industry's needs.  

3. Align with Decarbonization Goals: Ensure to choose a software that aligns with your company's decarbonization goals. Some software provides tools for energy management, waste management etc., which can help you in your decarbonization efforts.  

4. Check for Integration: It’s important the software integrates with your existing systems, including energy management, CRM, ERP and operation systems.  

5. Evaluate Features: Identify what features are important to you, these might include simple setup and usage, machine learning and AI capabilities, real-time monitoring, customizable alerts etc.  

6. Request a Demo/Trial: Almost every provider offers a free trial or demo. Make use of it to get a basic understanding of how the tool works and if it matches your requirements.  

7. Reviews and Feedback: Check out the reviews and feedback given by customers who have already used the software.  

8. Cost: Compare the pricing plans of different vendors and select one that gives you maximum features at a minimum cost.  

9. Support: Check the kind of after-sales support provided by the provider. Support can come in the form of training, documentation, online chat, email, or phone call.  

10. Negotiate: Once you select your vendor, negotiate the terms of the deal such as pricing, after-sales support, software upgrades etc.  

11. Implement: After finalizing, begin software implementation. This should be done in accordance at a pace that is comfortable for your company.  Remember, the effectiveness of the tool will greatly depend on how intuitively it can be integrated into your existing operational structure.

Predictive Maintenance Software can assist in decarbonization in several ways:  

1. Efficiency Improvement: By predicting when machinery or equipment needs maintenance or replacement, the software ensures that all equipment is running at maximum efficiency. Efficient machinery uses less energy, thus reducing carbon emissions.  

2. Reduce Waste: Predictive maintenance can identify parts or equipment that are wasting energy or operating inefficiently. By making these corrections, the system can minimize waste and decrease carbon emissions.  

3. Extend Equipment Lifespan: Predictive maintenance can significantly extend the life of machinery and equipment by ensuring that it is always working at optimum levels. Using equipment for a longer period of time means less manufacturing of new equipment, which in turn contributes to lower carbon emissions.  

4. Optimizing Inventory: Predictive maintenance software can predict when you will need new parts or replacements, which means you can avoid overstocking and thus reduce waste and the carbon emissions associated with producing more parts than necessary.  

5. Transport Emissions: By predicting which parts are necessary and when, you can bundle shipments and reduce the need for urgent, last-minute deliveries. This lowers overall shipping emissions by reducing the number of shipments needed.  

6. Data-Driven Decisions: By relying on software rather than manual inspections or routine-based maintenance, companies can base their decisions on extensive data, which often leads to more effective maintenance strategies and lower emissions.  Predictive maintenance software, then, contributes to the broader efforts of enterprises to monitor, manage and reduce their carbon footprint.