pushing docs updated (#508)

* pushing docs updated

* Fixed README.md logo

* Fixed README.md logo

* Fixed README.md spacing

* fixed tag line

* LLM router doc fixes

* minor logo and branding changes

* minor changes to the README

* minor changes to the README

---------

Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-329.local>

README.md

@@ -4,8 +4,9 @@
 <div align="center">
 
 
-_The AI-native proxy server for agentic applications._<br><br>
-Arch handles the **pesky**, low-level details like routing user prompts to the right agents or specialized Model Context Protocol (MCP) tools, providing unified access and observability to large language models (LLMs), and quickly clarifying vague user inputs. With Arch, you build faster by focusing on the high-level logic of agents.
+_The AI-native proxy server and the universal data plane for AI agents._<br><br>
+Arch handles the *pesky low-level work* in building AI agents like clarifying vague user inputs, routing prompts to the right agents, calling tools for simple tasks, and unifying access to large language models (LLMs) - all without locking you into a framework. Move faster by focusing on the high-level logic of your agents.
+
 
 [Quickstart](#Quickstart) •
 [Demos](#Demos) •
@@ -25,14 +26,14 @@ Arch handles the **pesky**, low-level details like routing user prompts to the r
 # Overview
 <a href="https://www.producthunt.com/posts/arch-3?embed=true&utm_source=badge-top-post-badge&utm_medium=badge&utm_souce=badge-arch&#0045;3" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=565761&theme=dark&period=daily&t=1742359429995" alt="Arch - Build&#0032;fast&#0044;&#0032;hyper&#0045;personalized&#0032;agents&#0032;with&#0032;intelligent&#0032;infra | Product Hunt" style="width: 188px; height: 41px;" width="188" height="41" /></a>
 
-Past the thrill of an AI demo, have you found yourself hitting these walls? You know, the all too familiar ones:
+AI demos are easy to build. But past the thrill of a quick hack, you are left building, maintaining and scaling low-level plumbing code for agents that slows down AI innovation. For example:
 
-- You go from one BIG prompt to specialized prompts, but get stuck building **routing and handoff** code?
-- You want use new LLMs, but struggle to **quickly and safely add LLMs** without writing integration code?
-- You're bogged down with prompt engineering just to **clarify user intent and validate inputs** effectively?
-- You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently?
+- You want to build specialized agents, but get stuck building **routing and handoff** code.
+- You want use new LLMs, but struggle to **quickly and safely add LLMs** without writing integration code.
+- You're bogged down with prompt engineering work to **clarify user intent and validate inputs**.
+- You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently.
 
-And you think to yourself, can't I move faster by focusing on higher-level objectives in a language/framework agnostic way? Well, you can! **Arch Gateway** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that:
+With Arch, you can move faster by focusing on higher-level objectives in a language and framework agnostic way. **Arch** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that:
 
 >Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) systems to improve speed and accuracy for common agentic scenarios  – all outside core application logic.*
 

docs/source/get_started/intro_to_arch.rst

@@ -2,18 +2,16 @@
 
 Intro to Arch
 =============
+AI demos are easy to build. But past the thrill of a quick hack, you are left building, maintaining and scaling low-level plumbing code for agents that slows down AI innovation.
+For example:
 
-Arch is an intelligent proxy server designed agentic applications. **Move faster** by letting Arch handle the **pesky heavy lifting** in building agents:
-fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs.
+- You want to build specialized agents, but get stuck writing **routing and handoff** code.
+- You bogged down with prompt engineering work to **clarify user intent and validate inputs**.
+- You want to **quickly and safely use new LLMs** but get stuck writing integration code.
+- You waste cycles writing and maintaining **observability** code, when it can be transparent.
+- You want to **apply guardrails**, but have to write custom code for each prompt and LLM.
 
-Past the thrill of an AI demo, have you found yourself hitting these walls? You know, the all too familiar ones:
-
-- You break a prompt into specialized ones, but **get stuck writing routing** and handoff logic?
-- You want use new LLMs, but **struggle to quickly add LLMs** without writing integration logic?
-- You're **trapped in tedious prompting work** to clarify inputs and user intents?
-- You're **wasting cycles** choosing and integrating **code for observability** instead of it just happening transparently?
-
-And you think to yourself, can't I move faster by focusing on higher-level objectives in a language and framework agnostic way? Well, you can!
+Arch is designed to solve these problems by providing a unified, out-of-process architecture that integrates with your existing application stack, enabling you to focus on building high-level features rather than plumbing — all without locking you into a framework.
 
 .. figure:: /_static/img/arch_network_diagram_high_level.png
    :width: 100%
@@ -22,7 +20,7 @@ And you think to yourself, can't I move faster by focusing on higher-level objec
    High-level network flow of where Arch Gateway sits in your agentic stack. Designed for both ingress and egress prompt traffic.
 
 
-**Arch Gateway was built by the contributors of Envoy Proxy with the belief that:**
+Arch is an AI-native proxy server and the universal data plane for AI built by the contributors of Envoy Proxy with the belief that:
 
   *Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests
   including secure handling, intelligent routing, robust observability, and integration with backend (API)
@@ -41,8 +39,8 @@ This gives Arch several advantages:
 
 * Arch can be deployed and upgraded quickly across your infrastructure transparently without the horrid pain of deploying library upgrades in your applications.
 
-**Engineered with Fast LLMs:** Arch is engineered with specialized small LLMs that are designed for fast, cost-effective and accurate handling of prompts.
-These LLMs are designed to be best-in-class for critical prompt-related tasks like:
+**Engineered with Fast Task-Specific LLMs (TLMs):** Arch is engineered with specialized LLMs that are designed for the fast, cost-effective and accurate handling of prompts.
+These LLMs are designed to be best-in-class for critical tasks like:
 
 * **Function Calling:** Arch helps you easily personalize your applications by enabling calls to application-specific (API) operations via user prompts.
   This involves any predefined functions or APIs you want to expose to users to perform tasks, gather information, or manipulate data.

docs/source/get_started/overview.rst

@@ -3,10 +3,10 @@
 
 Overview
 ============
-Welcome to Arch, The intelligent (edge and LLM) proxy server for agentic applications.
+`Arch <https://github.com/katanemo/arch>`_ is an AI-native proxy server and the universal data plane for AI - one that is natively designed to handle and process AI prompts, not just network traffic.
+
+Built by contributors to the widely adopted `Envoy Proxy <https://www.envoyproxy.io/>`_, Arch helps you move faster by handling the pesky *low-level* work in AI agent development—fast input clarification, intelligent agent routing, seamless prompt-to-tool integration, and unified LLM access and observability—all without locking you into a framework.
 
-Move **faster** by letting Arch handle the pesky heavy lifting in building agents: **fast input clarification**, **agent routing**,
-seamless integration of prompts with **tools for common tasks**, and **unified access and observability of LLMs**.
 
 In this documentation, you will learn how to quickly set up Arch to trigger API calls via prompts, apply prompt guardrails without writing any application-level logic,
 simplify the interaction with upstream LLMs, and improve observability all while simplifying your application development process.

docs/source/guides/llm_router.rst

@@ -3,7 +3,12 @@
 LLM Routing
 ==============================================================
 
-LLM Router is an intelligent routing system that automatically selects the most appropriate large language model (LLM) for each user request based on the intent, domain, and complexity of the prompt. This enables optimal performance, cost efficiency, and response quality by matching requests with the most suitable model from your available LLM fleet.
+With the rapid proliferation of large language models (LLM) — each optimized for different strengths, style, or latency/cost profile — routing has become an essential technique to operationalize the use of different models.
+
+Arch Router is an intelligent routing system that automatically selects the most appropriate LLM for each user request based on user-defined usage preferences. Specifically Arch-Router guides model selection by matching queries to user-defined domains (e.g., finance and healthcare) and action types (e.g., code generation, image editing, etc.).
+Our preference-aligned approach matches practical definitions of performance in the real world and makes routing decisions more transparent and adaptable.
+
+This enables optimal performance, cost efficiency, and response quality by matching requests with the most suitable model from your available LLM fleet.
 
 
 Routing Workflow

docs/source/index.rst

@@ -9,14 +9,14 @@ Welcome to Arch!
 
    <div style="text-align: center; font-size: 1.25rem;">
    <br>
-   <p>Build <strong>fast</strong>, <strong>observable</strong>, and <strong>personalized</strong> GenAI apps</p>
+   <p>Build <strong>faster</strong>, <strong>multi-LLM</strong> agents for the <strong>enterprise</strong>.</p>
    </div>
 
    <a href="https://www.producthunt.com/posts/arch-3?embed=true&utm_source=badge-top-post-badge&utm_medium=badge&utm_souce=badge-arch&#0045;3" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=565761&theme=dark&period=daily&t=1742433071161" alt="Arch - Build&#0032;fast&#0044;&#0032;hyper&#0045;personalized&#0032;agents&#0032;with&#0032;intelligent&#0032;infra | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
-`Arch <https://github.com/katanemo/arch>`_ is an intelligent (edge and LLM) proxy, exclusively designed for prompts and agents - and built by the contributors of the widely adopted and loved `Envoy <https://www.envoyproxy.io/>`_ ).
+`Arch <https://github.com/katanemo/arch>`_ is an AI-native proxy server and the universal data plane for AI - one that is natively designed to handle and process AI prompts, not just network traffic.
 
-**Move faster** by letting Arch handle the **pesky heavy lifting** in building agents: fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs - all outside business logic.
+Built by contributors to the widely adopted `Envoy Proxy <https://www.envoyproxy.io/>`_, Arch helps you move faster by handling the pesky *low-level* work in AI agent development—fast input clarification, intelligent agent routing, seamless prompt-to-tool integration, and unified LLM access and observability—all without locking you into a framework.
 
 .. tab-set::