Update README.md

Author: kichanyurd

README.md

@@ -2,7 +2,7 @@
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 <img alt="Parlant Logo" src="https://github.com/emcie-co/parlant/blob/70757094103f6cc50e311edaeb0729e960fbcb56/logo.png" width="125" />
   <h3>Parlant</h3>
-  <p>A feedback-driven approach to building and guiding customer-facing AI agents</p>
+  <p>A structured approach to building and guiding customer-facing AI agents</p>
   <p>
     <a href="https://www.parlant.io/" target="_blank">Website</a> |
     <a href="https://www.parlant.io/docs/quickstart/introduction" target="_blank">Introduction</a> |
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 ## What is Parlant?
-With Parlant's API, you can easily create and serve guided Conversational AI to your customers, and continuously improve it with feedback from customers and business experts.
+Parlant is a structured way to create and manage guided customer-facing AI agents. It lets you build robust agents from scratch; or, in more advanced cases, a robust interaction layer for your prebuilt agents.
+
+Structure is what lets Parlant get better accuracy than most other agentic frameworks. It allows Parlant to run pinpointed, real-time conformance checks that ensure your agents adhere to your instruction. It also gives you specific feedback on where agents may have misinterpreted your instructions, so you can quickly troubleshoot and improve.
+
+Just as importantly, Parlant's way of breaking behavioral guidance down to different elements helps it understand your intentions better. Using this understanding, Parlant actively gives you feedback on your configuration to help you maintain a behavioral configuration for your agents that's coherent and free of confusing contradictions.
 
 ## Why use Parlant?
 Building conversational AI agents is relatively simple for most developers—at least, it's relatively simple to build an initial prototype.
@@ -33,6 +37,12 @@ With DIY prompt-engineering, reliably incorporating feedback from stakeholders i
 
 Parlant bridges this gap by making it easy and fast for developers to adjust the behavior of AI agents reliably, allowing you to iterate quickly with feedback from customers and business stakeholders.
 
+## Real-world impact
+
+[Revenued](https://www.revenued.com), A business capital provider, could get into trouble if their AI agents make false claims or make statements that imply discrimination in lending.
+
+With Parlant, they've been able to quickly integrate feedback from customer service experts and then test and verify that the agents aren't making problematic promises or statements to customers.
+
 ## Key benefits
 
 ### Control that actually works
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 * **Debug with ease**: Troubleshoot effectively by tracing which guidelines were applied and why for any given response
 * **Test before deploy**: Validate changes using the built-in chat UI to test new behaviors before they reach customers
 
-## Real-world impact
-
-[Revenued](https://www.revenued.com), A business capital provider, could get into trouble if their AI agents make false claims or make statements that imply discrimination in lending.
-
-With Parlant, they've been able to quickly integrate feedback from customer service experts and then test and verify that the agents aren't making problematic promises or statements to customers.
-
 ## Works with all major LLM providers
 - [OpenAI](https://platform.openai.com/docs/overview) (also via [Azure](https://learn.microsoft.com/en-us/azure/ai-services/openai/))
 - [Gemini](https://ai.google.dev/)