How Converzaq reduces invented answers by grounding replies in business knowledge

Language models are good at sounding sure. Service businesses cannot afford that habit. A made-up price, a made-up warranty, or a made-up clinical suggestion creates a problem the owner has to unwind.

Converzaq’s countermeasure is the business knowledge you supply. Website pages, uploaded documents, services, hours, policies, and service area are the source. Retrieval pulls relevant pieces into the conversation so the answer is tied to your material rather than a generic trades script.

That does not make the system perfect. A messy website produces messy answers. If two pages disagree about emergency fees, the assistant can repeat the disagreement. Training is an editing job: remove the pages that are outdated and state the rule you want in one place.

The failure mode to design for is missing information. The correct reply is “I don’t have that published — someone from the team can confirm,” plus a captured lead. The incorrect reply is a confident number.

Structured extraction sits next to the reply. Even when the customer rambles, the lead should end up with fields: contact, need, location or patient status, urgency, and the next step. The prose summary is for a human. The fields are so the morning list is sortable.

Review a sample of transcripts after the first week. Every invented detail is a missing fact in the knowledge, not a reason to add more adjectives to the prompt.