Engineering Knowledge
Allow engineers and operators to interact with manuals, specifications, procedures, drawings and historical knowledge.
01Manufacturing × Engineering × AI
Industrial Intelligence.Built for Manufacturing.
Connect your processes, equipment, industrial data and engineering knowledge to AI systems designed for real manufacturing operations.
Industrial architecturelive signal
02Approach
AI Built Around
Your Manufacturing Operation.
01
Process Context
Understand how equipment, materials, parameters and manufacturing operations interact.
02
Industrial Knowledge
Connect manuals, SOPs, engineering information, operating standards, historical events and organizational knowledge.
03
Private Intelligence
Use private cloud, local infrastructure or on-premise AI where operational or confidentiality requirements demand it.
03Architecture
From Factory Data
to Industrial Intelligence.
Every layer is explicit: industrial systems, data, engineering knowledge, retrieval infrastructure, models, agents and the applications operators actually use.
L1
Industrial Environment
- PLC
- Sensors
- SCADA
- MES
- ERP
- Quality Systems
- Engineering Systems
L2
Industrial Data
- Time series
- Batch & lot
- Process parameters
- Events
L3
Engineering & Enterprise Knowledge
- Manuals
- SOPs
- Specifications
- Drawings
- Process history
- Maintenance history
- Engineering knowledge
L4
Knowledge Infrastructure
- Document processing
- Embeddings
- Vector search
- Reranking
- Metadata
- Knowledge graphs
L5
Artificial Intelligence
- Large Language Models
- Machine Learning
- Computer Vision
L6
AI Agents
- Retrieval
- Analysis
- Reasoning
- Execution
L7
Industrial Applications
- Engineering Copilot
- Plant Knowledge
- Predictive Quality
- Process Optimization
Insight
Decision
Action
04Capabilities
Built for Real Industrial Problems.
Process Intelligence
Connect manufacturing variables and historical performance to identify patterns and improve processes.
Predictive Operations
Apply machine learning to quality, reliability, maintenance and process outcomes.
Agentic Workflows
Build AI agents capable of researching, analyzing, preparing information and executing repeatable workflows.
Computer Vision
Use visual AI for inspection, monitoring and defect identification.
Operational Excellence
Combine industrial engineering methods with AI to accelerate loss analysis, root cause analysis and continuous improvement.
05Stack
An AI Stack Designed
Around the Operation.
06
Applications
- Engineering Copilot
- Plant Knowledge Assistant
- Predictive Quality
- Process Optimization
- Root Cause Analysis
- Workflow Automation
05
Agents
- Engineering agents
- Research agents
- Quality agents
- Maintenance agents
- Operational agents
04
Intelligence
- LLMs
- Machine Learning
- Computer Vision
03
Knowledge Infrastructure
- Ingestion
- Embeddings
- Vector search
- RAG
- Reranking
- Knowledge graphs
02
Knowledge
- Manuals
- SOPs
- Engineering documents
- Specifications
- Historical information
- Operational knowledge
01
Industrial Systems
- PLC
- Sensors
- SCADA
- MES
- ERP
- Industrial databases
06Private / Local AI
Your Factory Knowledge
Doesn't Have to Leave
Your Environment.
Some industrial organizations require greater control over sensitive engineering, production and operational information. BSKLab designs the architecture around that requirement.
- Private cloud
- Customer-controlled infrastructure
- Local GPU systems
- On-premise models
- Controlled APIs
- Private RAG environments
Customer-controlled environment
Industrial Data
PLC · SCADA · MES · Quality
Engineering Knowledge
Manuals · SOPs · Drawings
Private AI
Local GPU · On-premise models
Applications
Copilots · Agents · Analytics
Controlled egressPrivate cloud · Controlled APIs · Private RAG
07Use cases
High-Impact Manufacturing
AI Use Cases.
Use case 01
Predictive Quality
Relate process parameters, materials and equipment behaviour to quality outcomes so deviations are anticipated instead of discovered at inspection.
08Method
Start With the Process.
Not the Model.
01
Understand
Understand the manufacturing process, business problem and operating environment.
02
Structure
Organize relevant data, documentation, equipment relationships and knowledge.
03
Connect
Connect the relevant systems, information sources and industrial data.
04
Build
Develop the appropriate AI, RAG, ML, vision or agent solution.
05
Deploy & Improve
Deploy, measure performance and continuously improve.
09Expertise
Manufacturing Experience
Meets AI Engineering.
A
Manufacturing
- Lean
- Six Sigma
- Industrial Engineering
- Manufacturing Engineering
- Operational Excellence
- TPM
- Process Optimization
- Quality Systems
B
Artificial Intelligence
- Machine Learning
- Large Language Models
- RAG
- Computer Vision
- Knowledge Graphs
- AI Agents
C
Industrial Technology
- Automation
- Controls
- Industrial Data
- MES / SCADA
- Edge Computing
- Local AI Infrastructure
10Explore
Inside BSKLab
Follow what we're researching, building and learning across industrial AI.
11Next step
Build Intelligence
Around Your Operation.
Explore how industrial data, engineering knowledge and artificial intelligence can work together to improve manufacturing operations.