Overview

Asset MRO software vendors often face requests from clients to provide detailed, customizable reports that track maintenance schedules, repair history, and operational efficiency. However, many of their end-users—such as maintenance managers—are not technically proficient in SQL or complex BI tools. Our AI-powered reporting tool solves this issue by allowing MRO software vendors to embed a user-friendly reporting solution, enabling non-technical users to generate custom reports with ease.

Business Challenge

When asset managers or maintenance teams need custom reports on asset performance, downtime, or maintenance costs, they often rely on MRO software vendors to build or modify reporting features. This leads to significant delays as the vendor’s development team must code and implement these requests. For the vendors, this increases development overhead, while for the client, it slows down the decision-making process.

Solution:

By embedding our AI-powered reporting tool into MRO software, vendors can provide their clients with a powerful and flexible reporting engine. Non-technical users can query the system using natural language commands, allowing them to create tailored reports on asset health, repair history, or operational downtime—without waiting for software updates.

Example Queries:

  • “Show me the repair history for all assets this quarter.”
  • “Generate a report on maintenance costs by department for the last year.”

This solution reduces dependency on custom development, enabling maintenance teams to make faster, more informed decisions.

Key Features

  • Natural Language Querying: Maintenance managers can request custom reports using plain language, eliminating the need for technical knowledge.
  • Custom Report Generation: From asset health to repair schedules, the tool generates insightful reports based on user queries.
  • Seamless Integration: The tool embeds easily into existing MRO software, providing a flexible and scalable reporting solution with no additional development required.