Free tool · Decision tree
RAG, fine-tuning or just a better prompt?
Up to four yes/no questions. You’ll get a recommendation and the next step to validate it — before anyone spends money on the wrong approach.
RAG, fine-tuning or prompting?
Does the model need knowledge it doesn’t have — private, recent or frequently changing information?
Want the full reasoning behind each branch? Read RAG vs fine-tuning vs prompting: stop paying for the wrong one.
Keep reading
GuideRAG vs fine-tuning vs promptingRAG adds knowledge, fine-tuning changes behaviour, prompting is where you start. How to choose — with a decision tree, costs and pitfalls.ServiceRAG developmentRAG development: AI assistants that answer from your documents and data with citations, permissions and measured accuracy — built in your cloud.GuideLLM evals for non-ML teamsHow to evaluate an LLM feature without a data-science team: build a test set, choose metrics, use LLM-as-judge carefully, run evals in CI and read the results.
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