Magic AI positions itself as a team member rather than a tool – an assistant trained on your own documents and data so it answers from what your organisation actually knows.
That framing points at the practical gap in general assistants: a model with no access to your internal material can only answer generically, and the useful questions inside a company are all specific. Grounding responses in your own corpus is what turns an assistant from a curiosity into something a team consults.
It ships with API access and documentation for embedding into your own products, a live demo to try before committing, and published pricing – all three unusual enough in this category to note. As with any document-grounded assistant, answer quality tracks the quality and currency of what you feed it, and outdated source material produces confidently outdated answers.
