How to prepare your Business Brain for useful AI answers
A business AI assistant needs current facts and clear rules before it can give useful customer answers. Start with your services, prices, opening hours, policies and escalation contacts, then test questions against those facts rather than judging only how polished an answer sounds.
Give each fact a source and an owner
Collect the information customers ask for repeatedly: services, locations, hours, eligibility, current prices, availability rules and refund policies. Identify the document or person responsible for each answer and record when it was checked.
Remove contradictory or expired versions. If two documents disagree, resolve the business rule before adding both. A model cannot decide which old price your business meant to keep. Avoid adding unnecessary personal data to general business knowledge.
Separate an answer from an action
Writing a reply is different from booking, charging, calling or publishing. Specify which actions need owner approval and what the assistant must do when a provider is unavailable. A confident sentence saying booked is not evidence that a booking exists.
For Woro, check which connected tools and permissions are available in the workspace. Website publishing, message delivery, voice and provider access have separate states. Ask for the actual result or failure reason rather than treating drafted text as completed work.
Build a small evaluation set
Write realistic questions with expected facts: opening hours, price exclusions, unsupported services, an ambiguous request and a request needing a person. Include an outdated document, a missing fact and text attempting to override the business rules.
Score factual correctness, whether the answer cites or reflects the right source, whether it admits missing information, and whether it escalates appropriately. Keep the question and observed result so you can repeat the evaluation after changing knowledge or models.
Review outcomes after launch
Review a sample of actual conversations with appropriate access controls and privacy protections. Correct the underlying fact or workflow when an answer fails; repeatedly rewriting a prompt can hide a missing integration.
Measure successful delivery and useful customer outcomes separately from generated answers. No model choice removes the need for tenant isolation, consent, spending controls and human review. This guide is a preparation checklist, not a claim that every Woro channel or tool is fully verified.
Questions people ask
Do I need to train a model to add my prices?
Usually the first step is maintaining reliable business knowledge and retrieving it for answers. Model training is a separate decision and does not replace current source data.
What should happen when the assistant does not know?
It should say what is missing and ask a useful question or hand the conversation to a person, rather than inventing a policy or claiming an action happened.
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