Building a Conversational AI Twin with ElevenAgents

Agent Configuration and Voice Cloning

To build a digital twin, the author uses the ElevenAgents platform to create a conversational agent. The process begins by selecting either a personal or business agent template, or starting from a blank configuration. The author clones their own voice by uploading approximately two hours of speech data into the ElevenLabs voice engine. Within the agent settings, the system prompt defines the agent's persona and business context, while the 'expressive mode' toggle is used to adjust the naturalness of the speech output.

Knowledge Base and Tool Integration

The agent's intelligence is powered by Retrieval Augmented Generation (RAG). The author populates the knowledge base by uploading transcripts from their YouTube videos specifically focused on RAG and agentic workflows. For functional capabilities, the agent is integrated with Calendly via the platform's tool-connection interface. This allows the agent to query availability and manage scheduling directly during a conversation. The platform also supports webhooks for retrieving external data or triggering actions on third-party websites.

Observability and Testing

The platform provides a branching feature similar to Git, allowing developers to test different agent configurations or workflows in parallel without affecting the production version. Once deployed, the dashboard offers observability metrics, including total call volume, LLM costs, and average response latency. Developers can also review logs of past conversations to debug failures or refine the system prompt based on real user interactions.