The case for a unified, transparent platform in conversational AI | Decagon

This post introduces a unified platform for conversational AI, detailing the capabilities for building agents with Agent Operating Procedures (AOPs), optimizing performance through simulations, guardrails, and live experimentation, scaling intelligently with analytics and self-improving knowledge systems, and deploying across chat, voice, and email with shared memory and context. It emphasizes the integration of product, CX, and engineering teams around a single source of truth, moving away from fragmented internal builds or black-box platforms.