Exploring the Technologies Behind Industrial Intelligence.
BSKLab.ai investigates how artificial intelligence, manufacturing knowledge, industrial data and modern computing architectures can work together to improve industrial operations.
Notes, Experiments
and Technical Analysis.
Engineering notes from active investigation — not peer-reviewed publications. Where results are not measured, we say so.
Eight Lines
of Investigation.
Industrial RAG
Research how retrieval-augmented generation can provide AI systems with engineering and manufacturing context.
Manufacturing Knowledge Graphs
Explore structured relationships between processes, equipment, sensors, controls, documents and engineering knowledge.
Industrial AI Agents
Investigate agents capable of supporting engineering, quality, maintenance and operational workflows.
Local & Private AI
Evaluate local LLMs, GPU infrastructure, inference architectures and private industrial AI deployments.
Industrial AI IOT
Evolving from predictive manufacturing models toward live industrial data: sensors, edge collection, IIoT signals and connected equipment feeding predictive quality and reliability.
Physical AI
AI embodied in the physical world — computer vision, autonomous driving, autonomous flight, robotics, and perception-driven action in manufacturing environments.
AI + Operational Excellence
Investigate how AI can augment Lean, Six Sigma, Industrial Engineering and continuous improvement workflows.
Semantic / Digital Twin
Evolving from capturing industrial knowledge toward structured semantic models of the plant: digital twins, knowledge graphs of the physical factory, and machine-readable representations of manufacturing reality.
From Investigation
to Working Prototype.
Research findings move into Labs, where they become prototypes tested against real manufacturing conditions.