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emcie-co/parlant: LLM agents built for control. Designed for real-world use. Deployed in minutes.

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Sound familiar? You're not alone. This is the #1 pain point for developers building production AI agents. Parlant flips the script on AI agent development. Instead of hoping your LLM will follow instructions, Parlant ensures it. Journeys: Define clear customer journeys and how your agent should respond at each step. Behavioral Guidelines: Easily craft agent behavior; Parlant will match the relevant elements contextually. Tool Use: Attach external APIs, data fetchers, or backend services to specific interaction events. Domain Adaptation: Teach your agent domain-specific terminology and craft personalized responses. Canned Responses: Use response templates to eliminate hallucinations and guarantee style consistency. Explainability: Understand why and when each guideline was matched and followed. That's it! Your agent is running with ensured rule-following behavior. Companies using Parlant: Financial institutions • Healthcare providers • Legal firms • E-commerce platforms "By far the most

Looking for an open-source alternative to Ada, Decagon, or Sierra? Parlant is production-ready. It streamlines the development and maintenance of enterprise-grade B2C (business-to-consumer) and sensitive B2B interactions that need to be consistent, compliant, on-brand, and comprehensively traceable. Why Parlant? Conversational context engineering is hard because real-world interactions are diverse, nuanced, and non-linear. ❌ The Problem: What you've probably tried and couldn't get to work at scale System prompts work until production complexity kicks in. The more instructions you add to…

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