Glossary cluster · 10 terms
What separates serious enterprise AI from a demo: vertical and domain-specific systems, agentic AI, semantic reasoning, and the platforms that ground it.
Agentic AI is artificial intelligence that pursues a goal across multiple steps, planning actions, using tools, and adapting to results rather than producing a single response to a single prompt.
An AI agent is a software system that perceives its context, decides on actions, and carries them out toward a goal, often using external tools and data sources and adjusting its approach based on what it observes.
A compound AI system is an architecture that combines multiple components — models, retrieval, tools, and structured knowledge — into one coordinated system, rather than relying on a single language model to handle every task.
A digital transformation platform is an integrated software environment that helps an organisation plan, execute, and track large-scale change, connecting strategy, methods, and delivery in one system rather than a patchwork of disconnected tools.
Domain-specific AI is artificial intelligence tuned to a defined body of knowledge, using the concepts, terminology, and relationships of a particular field so its reasoning stays accurate and relevant within that domain.
Enterprise AI is the application of artificial intelligence to core business operations at organisational scale, built to meet the security, governance, and reliability standards that large companies require rather than the loose expectations of consumer tools.
Knowledge management is the practice of capturing, organising, and making an organisation's collective expertise accessible, so that what people know is retained, reused, and applied consistently across the business.
Knowledge-grounded AI is artificial intelligence that bases its output on a defined, verifiable body of knowledge, so answers can be traced to source material rather than generated from the model's general training alone.
Semantic AI is artificial intelligence that reasons over the meaning and relationships between concepts, using structured knowledge such as a knowledge graph or ontology to guide understanding rather than relying on statistical patterns alone.
Vertical AI is artificial intelligence purpose-built for a specific industry or function, combining domain knowledge, specialised data, and tailored workflows to solve problems that a general-purpose model handles poorly on its own.
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Where Axibra sits
Axibra is the enterprise case these terms describe: vertical, grounded, compound, and auditable end to end.