CONCEPTS
Understand AI by seeing how it works.
Three core concepts, one chain from data to action. Each takes 3–5 minutes — enough to see how an enterprise AI system actually works.
Ontology: Giving AI a Model of the Enterprise, Not Just Its Data
- What is it?
- Giving AI a model of the enterprise, not just its data.
- Why does it matter?
- Through one real cost inquiry, see why AI still gets it wrong when all the data is there — and how an Ontology adds the missing relationship layer.
See it in action
Digital Employee: From Answering Questions to Getting Work Done
- What is it?
- From answering questions to getting work done.
- Why does it matter?
- A digital employee is not an upgraded chatbot: it takes on business responsibility within clear boundaries — triggered by events, grounded in enterprise context, verifying results, and executing governed actions after human confirmation.
See it in action
Agent: How AI Moves from Goals to Actions
- What is it?
- How AI moves from goals to actions through planning, tools, and decisions.
- Why does it matter?
- An agent is not a smarter chatbot: it pursues a goal by selecting and executing actions, observing results, and adapting its next steps. Walk through the full Goal → Plan → Tool → Observe → Decide → Re-plan loop interactively.
See it in action
SCENARIO 01
BOM Cost Analysis: why did the new product become more expensive?
All three concepts on one stage: from a cost inquiry in a product-line review, trace the root cause through Ontology → Digital Employee → Agent.
Enter the scenario
Concept Connections
These concepts are not isolated — together they form the full chain of an enterprise AI system, from understanding the world to getting work done.
Ontology gives the Digital Employee a model of the enterprise to work within — roles with context, actions with boundaries.
An Agent needs a model of the enterprise to reason about business objects and relationships.
The Digital Employee defines the role and boundaries. The Agent defines how the work gets done.