Glossary
Official definitions for Tezign products, models, architecture, and enterprise agent engineering.
Standalone Tezign products for professionals, teams, and small and medium-sized businesses, including Atypica, MuseDAM, Clipo, and MuseAI. Prosumer is the internal portfolio category; customer-facing navigation uses For Professionals.
Tezign’s Enterprise Agentic AI System. It connects the Context System, two core models, the Long-Horizon Agent Runtime, and enterprise agent foundations so agents can understand the enterprise and keep work moving.
AI systems that act continuously toward goals within enterprise context, permissions, and governance, collaborating with people and enterprise systems to deliver outcomes.
AI systems that plan around goals, use tools, maintain state, and adapt actions to outcomes. Their degree of autonomy should be governed by task risk, permissions, and human oversight.
Tezign’s core model for open-ended business problems, generating, evaluating, and dynamically converging across multiple possible paths rather than forcing every problem into one answer.
Tezign’s core model for simulating how people perceive, think, feel, and decide, helping teams form hypotheses, surface differences, and accelerate validation through real research.
Core technology within Tezign GEA. It connects enterprise content, data, rules, relationships, permissions, and decision trails into context that can be used and continuously updated.
A computable semantic network within the Context System that represents enterprise entities, relationships, provenance, permissions, state, and change over time.
Content, knowledge, decision rationale, feedback, and outcomes accumulated through enterprise operation so agents can inherit experience within authorized boundaries.
The runtime that preserves goals and state across interactions, workflows, and systems, with signal sensing, proactive initiation, pause, resume, retry, and human escalation.
An agent that does not only wait for a prompt, but can initiate authorized work from events and business signals or proactively bring a person in when judgment is needed.
The engineering foundations that let agents operate in real enterprise production environments: Agent Reliability & Evaluation, Security & Governance, and Enterprise Integration & Deployment. They are not standalone products; together they make Tezign GEA dependable, governable, and deployable at scale.
The engineering discipline for determining whether agents complete goals dependably through task-level evaluation, execution traces, observability, recovery, and outcome validation.
Identity, permission, data boundary, approval, audit, and human-accountability mechanisms governing what agents can see, invoke, and do.
Reusable packages of business capability and tool-use instructions that let agents take real action through APIs, MCP, events, or existing enterprise systems.
Human review, authorization, or takeover at high-risk, low-confidence, or judgment-intensive moments, keeping agent autonomy within explicit accountability boundaries.
A mechanism for agents with different roles and skills to divide work, exchange context, and coordinate execution toward a shared goal.
| Term | Definition |
|---|---|
| Prosumer Products | Standalone Tezign products for professionals, teams, and small and medium-sized businesses, including Atypica, MuseDAM, Clipo, and MuseAI. Prosumer is the internal portfolio category; customer-facing navigation uses For Professionals. |
| Tezign GEA | Tezign’s Enterprise Agentic AI System. It connects the Context System, two core models, the Long-Horizon Agent Runtime, and enterprise agent foundations so agents can understand the enterprise and keep work moving. |
| Enterprise Agentic AI | AI systems that act continuously toward goals within enterprise context, permissions, and governance, collaborating with people and enterprise systems to deliver outcomes. |
| Agentic AI | AI systems that plan around goals, use tools, maintain state, and adapt actions to outcomes. Their degree of autonomy should be governed by task risk, permissions, and human oversight. |
| Creative Reasoning Model | Tezign’s core model for open-ended business problems, generating, evaluating, and dynamically converging across multiple possible paths rather than forcing every problem into one answer. |
| Subjective World Model | Tezign’s core model for simulating how people perceive, think, feel, and decide, helping teams form hypotheses, surface differences, and accelerate validation through real research. |
| Context System | Core technology within Tezign GEA. It connects enterprise content, data, rules, relationships, permissions, and decision trails into context that can be used and continuously updated. |
| Context Graph | A computable semantic network within the Context System that represents enterprise entities, relationships, provenance, permissions, state, and change over time. |
| Enterprise Memory | Content, knowledge, decision rationale, feedback, and outcomes accumulated through enterprise operation so agents can inherit experience within authorized boundaries. |
| Long-Horizon Agent Runtime | The runtime that preserves goals and state across interactions, workflows, and systems, with signal sensing, proactive initiation, pause, resume, retry, and human escalation. |
| Proactive Agent | An agent that does not only wait for a prompt, but can initiate authorized work from events and business signals or proactively bring a person in when judgment is needed. |
| Enterprise Agent Foundations | The engineering foundations that let agents operate in real enterprise production environments: Agent Reliability & Evaluation, Security & Governance, and Enterprise Integration & Deployment. They are not standalone products; together they make Tezign GEA dependable, governable, and deployable at scale. |
| Agent Reliability & Evaluation | The engineering discipline for determining whether agents complete goals dependably through task-level evaluation, execution traces, observability, recovery, and outcome validation. |
| Security & Governance | Identity, permission, data boundary, approval, audit, and human-accountability mechanisms governing what agents can see, invoke, and do. |
| Agent Skills | Reusable packages of business capability and tool-use instructions that let agents take real action through APIs, MCP, events, or existing enterprise systems. |
| Human-in-the-loop | Human review, authorization, or takeover at high-risk, low-confidence, or judgment-intensive moments, keeping agent autonomy within explicit accountability boundaries. |
| Multi-agent Orchestration | A mechanism for agents with different roles and skills to divide work, exchange context, and coordinate execution toward a shared goal. |