Custom Knowledge Training

Cody trains on a business's own documents and data so its answers reflect that specific company rather than generic knowledge pulled from the open web. A Beam agent reads new source material as it's added to a shared drive or wiki, applies the approved rule for what should feed the assistant, such as an updated policy document, and updates Cody's training set accordingly. It can also notify a content owner once a refresh completes. Sensitive documents, or material that conflicts with what's already trained, are routed to a human before being added.

Conversational Query Handling

Cody answers questions from customers or staff based on what it has been trained on. A Beam agent reads incoming queries and Cody's responses, applies the approved rule for logging or follow up, such as recording every question about a specific product, and updates a shared record so the pattern of questions is visible. Where permissions allow, it can also flag a repeated question that has no good answer yet. Questions touching legal, financial, or medical specifics are routed to a human rather than answered automatically.

Low Confidence Escalation

When Cody's confidence in an answer falls below a set level, that response needs a second look before it reaches the person who asked. A Beam agent reads the confidence score attached to each answer, applies the customer's approved threshold, and routes anything below it to a human teammate along with the original question and Cody's draft response. It can also notify a manager if a topic keeps triggering low confidence answers, pointing to a gap in the training material. The final answer in every escalated case comes from a person, not the assistant.