Book an AI Reality Check

Glossary

Glossary

Plain-language definitions for agentic AI, RAG, governance and the Karnataka GCC market. The vocabulary behind the workflows we install.

A

Agent orchestrationAgent orchestration is the coordination layer that routes work across multiple AI agents and tools so a multi-step task completes reliably, handling state, retries, handoffs and stopping conditions.
Agentic AIAgentic AI is software that uses a language model to plan and carry out multi-step tasks by calling tools, observing the results, and choosing its next action in a loop.
AI governance frameworkAn AI governance framework is the documented set of policies, roles, controls and records that determine who may deploy an AI system, on what data, with what testing, and who is accountable when it fails.

E

G

Global capability centre (GCC)A global capability centre is an offshore entity a multinational owns and operates to run strategic functions such as engineering, analytics, finance and operations in-house, rather than outsourcing them to a third party.

H

Human in the loopHuman in the loop is a workflow design in which a person reviews, approves or corrects an AI system's output at defined checkpoints before it takes effect, keeping accountability with a human.

M

Model Context Protocol (MCP)The Model Context Protocol (MCP) is an open standard that defines how AI applications connect to external tools and data through one uniform interface instead of many bespoke integrations.

N

Nano GCCA nano GCC is a global capability centre with 5 to 50 employees, a category Karnataka's GCC Policy 2024–2029 names explicitly and supports with incentives carrying no minimum employment or investment threshold.

R

Retrieval-augmented generation (RAG)Retrieval-augmented generation (RAG) is a technique that fetches relevant passages from your own documents and supplies them to a language model as grounding before it generates an answer.

T

Tool useTool use is the mechanism by which an AI model calls external functions, APIs or data sources during a task, instead of answering only from what it learned in training.

V

Vector searchVector search retrieves information by comparing numerical embeddings for semantic similarity, finding passages that mean the same thing as a query rather than sharing its exact keywords.

W

Workflow absorptionWorkflow absorption measures whether AI has actually changed how work runs (steps redesigned, cycle time reduced, errors cut) as opposed to adoption, which only counts access such as seats and logins.

Put the concepts to work

We install working agentic workflows, not vocabulary. Book a free AI Reality Check.

Book an AI Reality Check