AnswersAI transformation
In short
Draw the line inside every layer of the stack, not between layers. Rent what improves without you, such as frontier models, compute and standard software. Own what your work creates: the model of your business, your evaluations, how you decide, your trained model weights and your workflow logic. Owning means being able to move it, which is different from building it all yourself.
| Layer | Rent | Own |
|---|---|---|
| Models | Frontier models from every lab, improving every few months. | Models trained on your data, with the weights. |
| Data and context | Connectors and infrastructure. | The model of your business and its decision rules. |
| Agents and workflows | The agent platform and its tooling. | Your instructions, workflow logic and evaluations. |
| Applications | Standard software for commodity work. | The apps that carry what sets you apart. |
Buying everything leaves the company's most valuable knowledge inside suppliers' products, on their terms. Building everything spends years on infrastructure that improves faster when someone else maintains it. The useful middle is a platform you control, with the assets your work creates kept as yours.
Can we export the context, instructions, evaluations and trained models? Can we use other models? Where does our data live, and is it used for training? Who runs the system after go-live? What happens if the supplier changes terms?
Fig provides the platform and the engineers, so the company does not build infrastructure from scratch, while the digital twin, instructions, evaluations and trained weights remain the company's own and run in its cloud or Fig's.
Rarely for the platform itself. In-house teams are best spent on what the business owns: its context, decisions and evaluations.
Ownership of the model of your business, your evaluations and your trained weights.
Yes, if what you buy lets you export what you create. Check that before signing.
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