Every maintenance activity adds new information to your CMMS: time spent, parts used, work performed, causes of failure, comments and associated documents. But this data can be spread across multiple fields, tabs and attachments. Coswin 8i AI features bring this information together and summarise it to produce clear, directly usable maintenance reports.
Valuable maintenance data that is often scattered
After every maintenance activity, technicians enter a wide range of information into the CMMS: time spent, parts used, work carried out, causes of failure and comments. They may also add photos and other documents relating to the work.
All this information progressively enriches the maintenance history. But when a maintenance manager needs to validate the work, or a technician looks back at the history several months later, understanding exactly what happened may mean searching through several different sources.
The data is there, but it may be spread across different fields, tabs, modules and attachments. This fragmentation can make it harder to use effectively.
Generate a concise report from maintenance activity data
Coswin AI features allow users to automatically generate a concise report based on all the information recorded during a maintenance activity.
They can use information about the resources involved and time spent, parts and consumables used, work carried out, as well as Effect / Symptom / Defect / Cause / Remedy data.
They can also take into account technicians’ comments and associated content such as documents, photos, scans, audio files and videos.
The AI brings this information together to produce a consistent, readable and directly usable report tailored to the user profile.
Get straight to the essential information
This summary makes the maintenance history easier to read. Users no longer need to move between several tabs to understand what happened during an intervention or search through attachments for relevant information.
AI features also remove the need to manually reword technical comments or correct typing errors and inconsistencies in the way information has been written.
Users immediately have access to a clear summary tailored to their needs and easy to consult in the maintenance history.
Preserve and develop maintenance knowledge
At Siveco Group, we believe artificial intelligence should do more than simply provide a way to query maintenance data. It should also help improve the quality and long-term value of that data.
Coswin 8i AI features use information already available in the CMMS, adapt the output to each organisation’s requirements and preserve the expertise provided by maintenance teams. They also help make maintenance histories more consistent, relevant and easier to analyse.
The aim is not to replace the experience and feedback of maintenance teams. It is to make better use of that knowledge by turning scattered information into lasting, usable knowledge that directly supports decision-making.
From raw data to usable information
A CMMS contains information in many different forms: entered or dictated data, maintenance reports, documents, photographs and attachments.
Coswin 8i AI features can understand, combine and rephrase these different types of content to provide clear, relevant information. This approach extends from document processing to mobile use with
Maintenance data is no longer simply stored in the CMMS: it becomes easier for teams to understand, find and use.