AI for Manufacturing

Predictive maintenance, automated quality control, intelligent production planning. We make your manufacturing data-driven — pragmatic, GDPR-compliant, and measurable.

35%

less unplanned downtime with predictive maintenance

85%

time saved in document processing

< 1%

error rate with AI-powered quality control

3–6 mo.

to positive ROI

Sound familiar?

We see these challenges in almost every manufacturing company.

Unplanned machine downtime

A single unplanned stop easily costs five-figure sums. Reactive maintenance means: you repair instead of produce.

Manual quality control

Visual inspections are slow, subjective, and error-prone. With increasing volumes, manual QC no longer scales — reject rates climb.

Paper-based order processing

Orders by fax, invoices by mail, data manually entered into ERP. Every media break costs time and produces errors.

Production planning by gut feeling

Capacity is planned by experience, not data. The result: overcapacity, bottlenecks, and missed delivery dates.

AI Solutions for Manufacturing

Four building blocks that can be used individually or combined.

Predictive Maintenance

Analyze sensor data, predict failures, plan maintenance — before the machine stops. Reduces unplanned downtime by up to 35%.

Sensor data integration (vibration, temperature, current)
ML models for anomaly detection
Automatic maintenance notifications
Machine health dashboard

AI-Powered Quality Control

Visual inspection with computer vision. Detects defects faster and more consistently than the human eye — every shift, every part.

Camera-based defect detection
Real-time classification (pass/fail)
Complete quality documentation
Integration with existing test stations

Automated Order Processing

Automatically recognize, extract, and book invoices, delivery notes, and orders into ERP. No more manual data entry.

OCR for invoices, delivery notes, orders
Automatic data extraction and validation
ERP integration (SAP, DATEV, Navision)
Error rate below 2%

Production Planning Optimization

Demand forecasts based on historical data, seasonality, and market trends. Optimal capacity utilization instead of gut feeling.

ML-based demand forecasting
Optimized sequencing
Reduced setup times
Real-time capacity overview

How an AI project in manufacturing works

Four phases — from free consultation to scaled solution.

1

Analysis

Free initial consultation (30 min). We understand your production, machines, and bottlenecks. You get an initial assessment of AI potential.

2

Pilot Project

Implementation of the most impactful use case in 4–8 weeks. Measurable proof with your real production data.

3

Integration

Connection to existing ERP, MES, and machine systems. GDPR-compliant data processing in European data centers.

4

Scaling

Roll out to more lines, plants, and processes. Training your team for independent operation.

Results from practice

Concrete results that manufacturing companies have achieved with our AI solutions.

Manufacturing Mid-sized machine builder, 180 employees

Challenge

Invoice processing took 3 days per batch. Manual data entry into ERP regularly caused errors.

Solution

AI-powered document recognition with automatic ERP posting. OCR + ML classification for all incoming documents.

85% time saved
< 2% error rate
Production Manufacturing company, 250 employees

Challenge

Frequent unplanned machine stops caused production losses and high repair costs.

Solution

Predictive maintenance with retrofit sensors on critical equipment. ML model detects anomalies 72h in advance.

35% less downtime
20% lower maintenance costs
Supplier Automotive supplier, 90 employees

Challenge

Manual visual inspection could no longer meet quality requirements with increasing production volumes.

Solution

Camera-based AI quality control with real-time classification directly on the production line.

< 1% error rate
100% inspection coverage

What can AI save in your production?

Calculate your savings potential in 2 minutes — free and no obligation.

FAQ: AI in Manufacturing

Answers to the most common questions.

What does an AI project in manufacturing cost?

Pilot projects start from €10,000. Typical projects with ERP integration range between €15,000 and €40,000. What matters is the ROI: our projects typically pay for themselves within 3–6 months.

Do we need a lot of data for AI in manufacturing?

Not necessarily. For document processing (OCR), you don't need any historical data. For predictive maintenance, we recommend at least 3 months of sensor data. We help you build the right data foundation.

Does AI work with older machines?

Yes. Older machines can be equipped with retrofit sensors (vibration, temperature, current). For document processing and production planning, machine age doesn't matter.

How does AI integrate with our ERP system?

We integrate with SAP, Microsoft Dynamics, DATEV, Sage, Navision, and many other systems — including older software without modern APIs. Integration is part of every project.

What about data protection and GDPR?

Data protection is our top priority. Production data stays in European data centers. Every project undergoes a GDPR pre-assessment. On request, we work with your data protection officer.

How quickly will we see results?

First results after 4–8 weeks in the pilot project. Quick wins like automated invoice processing show results after just 2–3 weeks. Predictive maintenance needs 2–3 months of learning time.

Can we use funding for the project?

Yes, many AI projects in manufacturing are eligible for funding. We support you with the assessment and application — BAFA, KfW, and state programs. More on our funding page.

Ready for AI in your production?

30-minute initial consultation — free and no obligation. We analyze your automation potential and show concrete next steps.