Agentforce Service Errors

This reference contains errors from Agentforce platform services, organized by service and error code. Documentation for each error includes possible causes, troubleshooting steps, and if necessary, when to reach out to Salesforce Customer Support and what information to provide.

Service	Description
Agent Service Reasoner Errors	The Agent SVC Reasoner service coordinates conversations between multiple agents to complete complex tasks. Errors from this service typically indicate that a request between agents was malformed or couldn’t be authenticated, that the agent or session couldn’t be found, or that the orchestration timed out or encountered an internal failure.
Authentication Service Errors	The Agentforce authentication service manages org provisioning and the credentials that allow Agentforce and Einstein AI features to operate. Errors from this service typically indicate that an org couldn’t be provisioned, that authentication credentials couldn’t be validated, or that a platform dependency the service relies on was temporarily unavailable.
Interactive Data Science Service Errors	The Interactive Data Science service is the backend infrastructure for Model Studio, where admins and data scientists create projects, connect data sources, and deploy custom models into Agentforce and Einstein AI features. Errors from this service typically indicate that a project request was invalid or referenced a resource that doesn’t exist, that the org isn’t enabled for the requested capability, or that a platform dependency the service relies on was temporarily unavailable.
Language Detection Service Errors	The language detection service identifies the language of text submitted through Agentforce and Einstein AI features. Errors from this service typically indicate that the input text was too short or the wrong type, that required parameters were missing, or that the pipeline configuration connecting language detection to other steps was incorrect.
ML Lake Service Errors	The ML Lake service manages data storage access for Einstein AI pipeline jobs. Errors from this service typically indicate that the request or org identifier was invalid, that credentials couldn’t be issued or aren’t authorized, or that the service was temporarily unavailable.
Model Builder Errors	The Model Builder service trains predictive AI models on your Data Cloud data. Errors from this service typically indicate that a training job request was invalid or missing required parameters, that a job or model artifact couldn’t be found, or that a platform dependency the service relies on was temporarily unavailable.