Editorial guide

Vision AI terminology, explained

Vision AI terminology becomes manageable when each term is tied to a visible task and an expected output. This guide defines the words most likely to appear in a product brief without implying that different vendors implement them identically.

Core terms

• Image classification: choose one or more labels for an image or item.
• Object detection: identify objects and their locations, often with boxes.
• Segmentation: distinguish regions or pixels, useful when boundaries matter.
• OCR: recognise text visible in an image or document; it may misread small, stylised, or obscured text.
• Image captioning: describe visible content in language.
• Embedding: represent content as numbers for similarity or retrieval; it is not a human-readable explanation.
• Vision-language model: process visual input with language prompts or outputs.

Terms that are often confused

Computer vision names a technical field; multimodal AI describes systems spanning input types; Vision AI is an applied umbrella. Compare the scopes in Vision AI versus computer vision and Vision AI versus multimodal AI.

Write a testable brief

State the input, target output, acceptable uncertainty, escalation rule, and reviewer. Then test representative examples, including difficult ones. How Vision AI works gives a practical process.

Boundary

Definitions do not establish accuracy, suitability, privacy compliance, or performance for a particular system. Check current vendor documentation and retain human review where mistakes matter.

Get early access

If visual marketing terminology needs to become a next action, get early access to CoraVision. The late-2026 beta is exploratory.

A practical takeaway

Start with the Vision AI overview for category context. Classification assigns a label; detection locates an item; segmentation marks pixels or regions; OCR extracts visible text; and a vision-language model connects visual input with language. What is Vision AI? explains why none of these terms alone describes the full business workflow.

One useful promise: A useful promise: use the task-to-output table below to replace ambiguous AI language with a brief another person can test.

Product boundaries

CoraVision is first-party product context, not independent research, a benchmark, a customer-result claim, or a promise of uplift. It is not a general Vision AI API. Capabilities, integrations, data handling, and beta access may change; confirm the current product scope before relying on it. Keep a human reviewer for consequential decisions and verify permissions, privacy, retention, and claims.

Get early access

If this direction fits your work, get early access to CoraVision for the exploratory late-2026 beta. Joining the list does not guarantee access, a feature, or an outcome.