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The CRM is usually the first place a business wants to apply automation and the place where mistakes are most expensive, because errors do not stay put. A bad record propagates into reporting, into sequences, and into what a salesperson says on a call. The useful distinction is between reading, drafting and writing, and they carry very different risk. Reading is nearly always safe Summarising an account history, surfacing which open deals have gone quiet, preparing a briefing before a call: all read-only, all immediately useful, none capable of damaging anything. This is where to start, and a surprising amount

A model that invents an answer is not malfunctioning. It is doing what it was built to do, which is produce plausible text. The engineering problem is to constrain where that behaviour can reach anything that matters, rather than to eliminate it. That reframing is useful, because it moves the work from prompt wording toward system design, which is where the reliable gains are. Ground the answer in retrieved source material The single largest reduction comes from giving the model the relevant material at question time and instructing it to answer only from that. Fabrication rates fall sharply when the

These two get compared as alternatives and they solve different problems. Retrieval augmented generation gives a model access to information it was never trained on. Fine-tuning changes how a model behaves. Choosing between them starts with deciding which of those you actually need. The question that settles it: is the model failing because it does not know something, or because it does not respond the way you want? Use retrieval when the model needs your facts If the system must answer from your documentation, your policies, your product catalogue or your case history, retrieval is the answer. The content stays