AI Glossary
What it means, why it matters to your business, and where it shows up in a real build decision.
In plain terms
A foundation model is a large, general-purpose AI model, such as GPT or Claude, trained once by a major lab and then adapted to many specific uses. Building on a foundation model means you rent proven capability instead of training from scratch, which is why serious AI features can now ship in weeks rather than years.
A foundation model is like a power grid. You do not generate electricity from scratch for every appliance. You tap into existing infrastructure and adapt it for your specific need.
A fintech company accesses an LLM via API to power its contract analysis feature, skipping the years and tens of millions of dollars it would cost to build a comparable model from scratch.
For almost all business AI use cases. Building from scratch is reserved for organizations with a specific data advantage, regulatory constraint, or extreme scale that justifies the cost.
When data sovereignty or industry regulation prohibits sending data to a third-party provider. In those cases, open-weight models running on your own infrastructure become the alternative.
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