Rasa is an enterprise-grade conversational AI platform designed to help organizations build AI agents that handle real-world conversation complexity at scale. The platform extends LLMs with business logic, structured flows, and deterministic control, enabling reliable agent behavior across millions of interactions. Rasa gives teams full visibility into how agents reason, respond, and perform, eliminating the black-box problem common in LLM-only approaches.

The platform includes a suite of capabilities: CALM (Conversational AI with Language Models) for combining LLM flexibility with deterministic logic, Enterprise RAG for real-time information retrieval from trusted data sources, NLU for intent-based dialogue structure, and a Voice module for real-time voice infrastructure with enterprise-grade speed. Omnichannel deployment is supported across text, messaging, voice, and IVR, with built-in turn-taking, timeout management, and latency control for voice interactions.

Rasa agents integrate with existing business systems and can be deployed on-premises, in the customer's own infrastructure, or through managed partner environments. The platform supports multilingual AI, enabling agents to adapt to language, tone, and context for global deployments. Agent orchestration capabilities allow coordination of multiple agents and tools to deliver contextually appropriate responses across complex workflows.

Enterprises using Rasa have reported a 50% reduction in operational expenses, a 59% goal completion rate per conversation, and a 4.4-star customer satisfaction score. Customers include Autodesk, BNP Paribas, Swisscom, T-Mobile, and ERGO Group, who use Rasa for customer support, sales enablement, employee experience automation, and operational efficiency.