Quantum Ontology
The conceptual model that defines how agents, automations, and entities operate inside Quantum's control plane.
Quantum is the control plane that orchestrates and governs AI agents and automations to generate measurable, secure, and scalable business impact.
1. What is Quantum?
Quantum Automation Center is Quantum's execution and governance platform. Its purpose is to orchestrate, govern, and optimize digital processes through a shared vocabulary for business objects, actions, rules, and impact events.
Orchestrates: coordinates workflows, automations, agents, data, and dependencies.
Governs: applies permissions, policies, limits, and controls in real time.
Optimizes: measures impact, learns from outcomes, and improves operations.
Outcome
Quantum turns business intent into reliable, traceable, and measurable execution.
2. Ontological model
Core entities and their relationship inside Quantum's control plane.
Control entities
Execution engines
Connectors and resources
3. Main entities
Organization: root container that groups teams, spaces, and policies.
Space: logical scope inside an organization for autonomous work.
Project: set of workflows, agents, and automations aligned to an objective.
Workflow: versioned sequence of deterministic steps that executes actions.
Agent: autonomous AI capability that interprets context, decides, and acts.
Automation: scheduled or triggered process that produces verifiable outputs.
4. Ontological principles
Abstraction
Clear separation between business intent and technical execution.
Isolation
Spaces and projects separate resources, data, and permissions.
Composition
Capabilities combine to create more complex behaviors.
Observability
Everything is measurable: state, performance, cost, quality, and impact.
Traceability
Each action, decision, and change is recorded for audit.
Continuous learning
The system learns from execution to improve results.
5. Key relationships
User belongs to an organization and can access multiple spaces.
Space contains projects with shared data, permissions, and goals.
Project groups workflows, agents, and automations for a capability.
Connectors connect workflows and agents with APIs, databases, files, and SaaS.
Policies apply across levels to guarantee security and compliance.
6. Capabilities enabled by the ontology
Scalability
Multi-level structure that grows without losing governance.
Security
Granular access control and policies by context.
Efficiency
Intelligent automation that reduces time and operating cost.
Observability
Complete visibility over execution and impact.
Extensibility
Connectors and APIs for any ecosystem integration.
Intelligence
Agents that learn, assist, and optimize outcomes.
7. Impact metrics
Every use case should demonstrate value through verifiable impact events.
Time saved
75-90%
Potential reduction in document drafting and preparation.
Avoided cost
COP / USD
Direct savings across processes and operating resources.
Efficiency
%
Improvement in cycle time, productivity, and compliance.
Executions
#
Volume and success across workflows, agents, and automations.
Business impact
KPI
Measurable outcomes on critical indicators.
8. Governance and security
RBAC role-based access control tied to responsibilities.
Policies configurable limits, quotas, and restrictions.
Audit immutable record of actions, changes, and decisions.
Compliance alignment with privacy and security standards.
Data sovereignty customer data remains bounded by clear ownership rules.
In summary
Quantum's ontology provides the shared language and structure needed to orchestrate people, processes, agents, and systems in an intelligent, secure, and measurable way.
Minimum model for declaring a capability
Every automation or agent should declare purpose, business objects, inputs, outputs, impact events, and associated governance.