Train agents on custom data sources

Chaindesk builds an agent's knowledge base from documents, URLs, or files a team uploads as data sources, which the agent then answers from. A Beam agent can add a new data source when fresh content becomes available, such as an updated help article or a new policy document, and trigger a resync so the Chaindesk agent's answers reflect it. Sources that fail to parse, come back empty, or contain content the format cannot read cleanly are flagged to a person to fix rather than left in the knowledge base silently broken.

Deploy approved agent configuration changes

A Chaindesk agent's behavior, such as its instructions, tone, and which data sources it draws from, can be updated and republished as requirements change. An agent can apply an approved configuration change, for example adding a new data source to an existing agent or adjusting its instructions, and push the update live to wherever the agent is deployed, such as a website widget. This lets configuration changes roll out without someone manually stepping through the builder each time. Any change that alters what the agent is allowed to say or promise to a customer is held for a person to approve before it goes live.

Monitor conversations for unresolved queries

Chaindesk logs the conversations its agents have with end users, and an agent can read these logs to check how the deployed agent is performing. It applies a rule the team has approved, such as flagging conversations where the agent could not answer from its data sources or where a user asked to speak to a person, and updates a tracking record accordingly. This surfaces gaps in the knowledge base and unresolved queries without someone reading every transcript. Conversations that the rule flags as unresolved or escalated are routed to a human support agent to pick up and continue.