Section Overview
AI Concepts Overview
AI concepts define the core building blocks used in production AI systems.
This section matters because clear conceptual understanding prevents costly implementation mistakes.
Section Navigation
Agents and Orchestration
Agent behavior, orchestration patterns, and control logic.
What Are AI Agents
AI agents are software systems that can interpret context, choose actions, use tools, and continue until a task is complete or escalation is required. The ke...
What Is Agent Orchestration
Agent orchestration is the coordination layer that manages how one or more AI agents plan, delegate, execute tools, and return outcomes inside a controlled w...
What Is Agentic AI
Agentic AI describes systems that can set intermediate goals, choose actions, use tools, and adapt based on feedback rather than only generating one-shot res...
What Is AI Orchestration
AI orchestration is the process of coordinating prompts, models, tools, and business logic into deterministic workflows that deliver reliable outcomes.
Data and Retrieval
Data readiness, retrieval design, and knowledge access layers.
What Is a Vector Database
A vector database is a specialised storage and retrieval system built to store high-dimensional numerical vectors — called embeddings — and run fast similari...
What Is AI Data Pipeline
An AI data pipeline is the end-to-end system that collects, validates, transforms, and serves data so AI models and retrieval systems can operate reliably in...
What Is RAG
RAG stands for Retrieval-Augmented Generation. It is an architecture pattern where a language model retrieves relevant context from a trusted knowledge base...
Model Lifecycle
Training, inference, monitoring, drift, and fine-tuning operations.
What Is Fine-Tuning
Fine-tuning is the process of continuing to train a pre-trained foundation model on a task-specific dataset so the model's weights are adjusted to produce ou...
What Is Model Drift
Model drift is the degradation of model performance over time due to changes in the real-world conditions the model was trained on. A model that performs wel...
What Is Model Inference
Model inference is the runtime process where a trained model receives input and produces predictions or generated output for a live workload.
What Is Model Monitoring
Model monitoring is the continuous measurement of deployed model behaviour, output quality, and risk signals after launch. It is categorically different from...
What Is Model Training
Model training is the process of fitting model parameters to data so the model can generalize to new inputs and support production decision tasks.
Infrastructure and Platforms
Foundation infrastructure, platform strategy, and runtime operations.
What Is AI Infrastructure
AI infrastructure is the compute, storage, networking, serving, and observability foundation required to train, deploy, and operate AI workloads at scale.
What Is AI Observability
AI observability is the ability to understand what is happening inside an AI system — not just whether it is up or down, but why it is producing the outputs...
What Is AI Platform
An AI platform is the integrated environment used to build, deploy, monitor, and govern AI applications across the model lifecycle.
Governance and Risk
Policies, controls, and responsible AI operating models.
Workflow and Decision Concepts
Concepts that connect AI logic to business workflows and outcomes.
What Is AI Automation
AI automation combines workflow automation with AI decision capability so repetitive or judgment-heavy tasks can be executed faster, with consistent quality...
What Is AI Workflow Automation
AI workflow automation applies AI decisions inside operational workflows so systems can complete end-to-end processes with fewer manual steps and higher cons...
What Is Decision Intelligence
Decision intelligence combines data, analytics, AI, and decision design so organizations can improve recurring business decisions with measurable outcomes.
Additional Pages
Additional supporting pages in this section.