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A large AI model trained on broad data at scale, designed to be adapted for a wide range of downstream tasks. Foundation models — such as GPT-4, Claude, or Gemini — learn general capabilities during training, then get specialized through fine-tuning or prompting. Most AI products you buy or build today sit on top of a foundation model developed by a third party. This creates a dependency risk: your product's behavior is partly determined by a model you do not control.
Why this matters for your team
Every AI product you buy is built on a foundation model you don't control. Before adopting any AI tool, ask which foundation model it uses and review that model's terms — your product's data handling and behavior are partly determined by a third-party model.
A startup building an AI contract review tool uses Claude as its foundation model, meaning it inherits both Claude's capabilities and Anthropic's data handling practices.