KnowFab GmbH i.G. · Leipzig

Explainable AI for engineering, quality, and production

We make industrial decisions faster, more robust, and more economical without replacing existing workflows.

Get in touchAbout us
The objective is data-driven decision support with transparent results in day-to-day operations.
Focus on industrial AI
Hybrid approach combining knowledge graphs and neural networks
Step-by-step integration into existing production workflows
Proven potential from real-world projects
−50 %*
Inspection effort
−90 %*
Engineering effort
100 %*
Process transparency
−30 %*
Energy costs

* Potential figures derived from completed project deployments. Results depend on process maturity, data quality, and integration scope.

What makes us different

More data. More context. More robust decisions.

Our hybrid approach processes process, quality, and context data together instead of isolated single signals. That creates artificial intelligence that can capture more relationships and deliver technically robust statements.

Our know-how

Artificial intelligence for real industrial processes

We connect more data sources than isolated point solutions and structure them with technical domain knowledge. The result is not an abstract score but a robust basis for decisions in engineering, quality, and production.

Built for
EngineeringQualityProduction
Why this makes a difference

More context can be processed

We can include more relevant data in one decision than approaches that only look at a few isolated signals.

Less black box

Results remain technically interpretable for engineering, QA, and production and therefore usable in daily work.

More operational relevance

Data becomes robust guidance that can be processed and operationalized in real production environments.

Typical point solution

Few signals, little context

  • often evaluates process data in isolation
  • separates quality, material, and equipment knowledge
  • often delivers only a score without technical framing
KnowFab hybrid approach

More context for robust decisions

01More data sources

Process, quality, material, and equipment context become usable together instead of being viewed separately.

02Technical context

Data is structured through domain knowledge, rules, and process logic so that relationships remain technically robust.

03Robust statement

The output is a traceable assessment with cause and possible corrective action instead of a pure black-box score.

Explore the hybrid approach
Solutions

Three building blocks in progress

Standardized products for scalability, complemented by project work for fast practical adoption.

KnowFab Design

KnowFab Design

Digital support for planning and evaluating production and joining processes.

Entry product with low implementation effort
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KnowFab JoinTech

KnowFab JoinTech

Analysis and monitoring of live production processes to reduce scrap and rework.

Usage-based licensing model
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Project business

Custom Projects

Tailored AI solutions to build references and continuously improve products.

Long-term focus on scalable product business
Discuss use case
Newsroom

Latest updates

Short updates on development, pilot initiatives, partnerships, and technical framing.

Automated production line used as the header image for KnowFab's founding article
2026-03-13 · Company News

KnowFab GmbH i.G. starts in Leipzig

With KnowFab GmbH i.G., we are starting in Leipzig. We are building explainable industrial AI for engineering, quality, and production with a clear focus on transparent decisions instead of black-box analytics.

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