Custom AI Development Company in Dubai

When the tool solves most of the problem and the remaining part is the part that matters — your domain language, your document formats, your compliance constraints, or a feature that has to live inside your own product. If a SaaS tool does the whole job, we say so during discovery and you should buy it.

Retrieval-augmented generation looks up the relevant passages from your own documents and gives them to the model to answer from, so the answer is grounded in your content rather than the model's general knowledge. It is cheaper than fine-tuning, easier to keep current, and lets you show the source for every answer. Fine-tuning is reserved for cases where retrieval demonstrably is not enough.

Against an evaluation set built from your real cases before any model is chosen — real documents, real questions, the answers your experts agree are correct. Accuracy is then reported per field or per task type, and the same set is re-run whenever a model or prompt changes. Reviewer corrections in production feed back into it.

The cheapest one that clears your accuracy bar on your evaluation set. That is usually decided per task rather than per project — a small model classifying documents, a larger one drafting a summary. Inference cost is engineered from the start, because a system that costs more per query than the work it replaces will be switched off within a year.

UAE or EU hosting regions by default, with a data processing agreement. If your sector needs residency inside the UAE, say so in discovery and it is architected in. The UAE PDPL governs how personal data is processed and transferred, and retrofitting residency later costs several times more than designing for it.