Answers

Should we fine-tune a model on our data instead?

Fine-tuning bakes yesterday's data into frozen weights: expensive to update, impossible to audit, unable to forget, and blind to permissions. Heidi keeps knowledge in a live memory the model reads at answer time, current, sourced, and deletable.

The operational problems are decisive. A fine-tuned model cannot tell you where an answer came from, cannot honor one person's access being different from another's, and cannot delete what a customer asks you to delete.
Context beats weights for company knowledge: it updates the moment something changes and improves automatically as frontier models improve, because Heidi rides the best available model instead of freezing one.

Related

Do Heidi's answers have sources?

Can Heidi forget things on command?

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