The Problem in Manufacturing

In modern production facilities, massive amounts of data are generated every day: machine running times, maintenance orders, inventory levels, quality inspections, spare parts consumption. This data is often found in various systems – ERP, MES, Excel spreadsheets, or even on paper lists.


This leads to typical challenges:

• Information is difficult to find and is limited to a few experts.

• Production employees wait a long time for evaluations, which then often have to be laboriously processed in Excel lists.

• Analyses are reactive – problems are recognized when it's already too late.

The consequences:

• Downtime and maintenance costs rise because patterns and trends are not recognized in time.

• Materials with limited shelf life are processed or written off too late.

• Quality issues cannot be systematically evaluated and resolved.

• Employee deployment and qualifications remain opaque.

How Scavenger AI Transforms Production

Scavenger AI connects directly with existing data sources – ERP, MES, or Excel – and enables complex production data to be analyzed in seconds. Instead of painstakingly querying databases manually, employees can ask questions in natural language and receive immediate answers – in tables, charts, or reports.

Examples:

• “Which materials in stock have a limited shelf life – and how old are they?”

• “Which three maintenance groups had the most activities last year?”

• “Which spare parts were used most frequently on line 17?”

• “When were spare parts with the material number 91673 last replaced?”

• “What reasons most frequently led to cancellations in quality orders?”

In the background, Scavenger automatically writes optimized code like an experienced data scientist – without hallucinations, but with precise results in seconds.

Benefits for Production Management

Executives finally have direct access to all relevant production data without relying on IT or BI departments.

Questions like these can be answered at any time:

• What is the average age of the machinery?

• Which components or parts cause the most repairs?

• Which production lines operate most efficiently?

The results can be immediately exported, shared, and integrated into decisions – whether in daily shop floor meetings or in strategic investment decisions.

Benefits for Employees in Manufacturing

Scavenger AI is not just a management tool – production employees also benefit directly.

Examples:

• Transparency about spare parts: Immediate queries about inventory levels and installed components.

• Better deployment planning: Overview of which employees with which qualifications are assigned to which tasks.

• Quick cause analysis: Immediate insights into frequent causes of errors or reasons for cancellations in quality processes.

This allows employees to make informed decisions and act proactively – instead of only reacting when problems have already escalated.

Conclusion: More Efficiency and Quality Through Data Intelligence

Scavenger AI transforms scattered production data into valuable recommendations for action.

• Management benefits from a clear overview of machines, materials, and processes.

• Employees receive a tool that supports them in their daily activities and makes decisions data-based.

The result: Less downtime, higher quality, and production that is no longer hampered by Excel lists but operates with data intelligence in real-time.