Parlant is an open-source control-layer framework designed to make customer-facing AI agents behave predictably and consistently. The core problem it addresses is that prompt engineering alone cannot guarantee reliable agent behavior across thousands of diverse conversations. Parlant introduces a declarative policy system where teams define behavioral guidelines, conversation boundaries, and response rules that the framework enforces at runtime regardless of how the underlying LLM might otherwise respond.
The architecture separates behavioral logic from language generation. Developers define policies covering topics like escalation triggers, prohibited responses, required disclaimers, tone guidelines, and multi-turn conversation flows. The framework evaluates each agent response against these policies before delivery, catching and correcting deviations in real time. This approach is fundamentally different from guardrails that only filter outputs — Parlant shapes the entire conversation trajectory based on declared business rules.
With over 17,000 GitHub stars, Parlant has gained significant traction among teams deploying agents in regulated or high-stakes customer interactions. The framework supports any LLM backend, integrates with existing chat infrastructure, and provides an audit trail of policy evaluations for compliance review. It is Apache 2.0 licensed and actively maintained with regular releases. Parlant fills a specific gap in the agent ecosystem between raw orchestration frameworks and output-only guardrails.
