Definitions

IDC’s glossary of essential technology and market terms — each entry defines a concept clearly, backs it with IDC research, and links to the data behind it. Browse the full list below, or search for a specific term.

IDC Quanta

• What Is IDC Quanta?

  IDC’s AI assistant for querying a subscriber’s entitled IDC research and data in natural conversation, returning cited, source-traceable answers.

• What Are IDC Quanta’s Five Pillars?

  The five approved design pillars behind IDC Quanta — Embedded, Contextual, Secure, Aware, and Rigorous — each with one canonical, one-line definition.

• What Is an AI-Native Intelligence Layer?

  A platform built from the ground up for conversational, structured-data access — not a chat interface added to a legacy research portal.

• What Is a Zero Data Leakage Workspace?

  A workspace where a customer’s queries, documents, and outputs stay isolated and are never used to train an AI model.

• What Is Data Provenance in AI Research?

  The ability to trace an AI-generated answer back to a specific, verifiable source — including which document, version, and date it came from.

• What Is the Model Context Protocol (MCP)?

  MCP is Anthropic’s open standard; IDC is building the first MCP server for the technology intelligence layer of the AI economy.

• How Does IDC Quanta’s Multi-Agent Pipeline Work?

  Every IDC Quanta answer passes through four specialized agents before it reaches you, including one that queries IDC’s canonical data directly.

• What Is an Agentic Workflow?

  Most AI tools answer questions. An agentic workflow executes the task end-to-end from a single prompt.

• What Is Entitlement Transparency in IDC Quanta?

  Entitlement transparency shows you exactly what your IDC subscription covers, and what it doesn’t, inside every IDC Quanta answer.