Technical standards for verifying the origin and authenticity of digital content, increasingly important for AI-generated media.
C2PA (Coalition for Content Provenance and Authenticity) is a standard for attaching verifiable metadata to images, video, and other content so consumers and platforms can understand how it was created and modified. Think of it as a tamper-evident “history” for media.
If you publish high-stakes media (press images, brand assets, product photography), provenance can help reduce misuse and improve confidence when content is syndicated across platforms.
Browse related definitions in the same glossary category.
AI Grounding
Techniques to anchor AI outputs in verified sources and facts, reducing hallucinations and improving reliability.
AI Hallucination
A phenomenon where a large language model generates false or illogical information but presents it as fact.
Citation Confidence
A measure of how accurately an AI model attributes information to its original source.
Embeddings
Numerical representations of text, images, or other data that capture semantic meaning, enabling similarity search and machine learning.
Fine-Tuning
Adapting a pre-trained AI model to a specific task or domain by training it on additional specialised data.
Large Language Model (LLM)
A type of AI model trained on vast text data to understand and generate human-like language, powering chatbots, content tools, and search features.
Related GEO services, audits, and frameworks that operationalise Content Provenance (C2PA) in commercial execution.
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