deploy: 1bbd35f1ab

build_with_arch/agent.html

@@ -412,7 +412,7 @@ the user’s intent.</p>
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build_with_arch/multi_turn.html

@@ -348,7 +348,7 @@ that you can test and modify locally for multi-turn RAG scenarios.</p>
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build_with_arch/rag.html

@@ -296,7 +296,7 @@ minutes. For additional details on how to build multi-turn RAG applications plea
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concepts/llm_provider.html

@@ -269,7 +269,7 @@ make outbound LLM calls.</p>
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concepts/prompt_target.html

@@ -366,7 +366,7 @@ Each parameter can be marked as required or optional. Here is a full list of par
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concepts/tech_overview/error_target.html

@@ -233,7 +233,7 @@ The errors are communicated to the application via headers like <code class="doc
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concepts/tech_overview/listener.html

@@ -237,7 +237,7 @@ address like <code class="docutils literal notranslate"><span class="pre">arch.l
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concepts/tech_overview/model_serving.html

@@ -224,7 +224,7 @@ how to generate API keys for model serving</p>
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concepts/tech_overview/prompt.html

@@ -398,7 +398,7 @@ This setup allows you to take advantage of Arch’s advanced traffic management
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concepts/tech_overview/request_lifecycle.html

@@ -398,7 +398,7 @@ processing request headers and then finalized by the HCM during post-request pro
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concepts/tech_overview/tech_overview.html

@@ -220,7 +220,7 @@
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concepts/tech_overview/terminology.html

@@ -217,7 +217,7 @@ and take appropriate actions.</p>
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concepts/tech_overview/threading_model.html

@@ -195,7 +195,7 @@ hardware threads on the machine.</p>
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get_started/intro_to_arch.html

@@ -157,16 +157,16 @@
 <div id="content" role="main">
 <section id="intro-to-arch">
 <span id="id1"></span><h1>Intro to Arch<a @click.prevent="window.navigator.clipboard.writeText($el.href); $el.setAttribute('data-tooltip', 'Copied!'); setTimeout(() =&gt; $el.setAttribute('data-tooltip', 'Copy link to this element'), 2000)" aria-label="Copy link to this element" class="headerlink" data-tooltip="Copy link to this element" href="#intro-to-arch"><svg height="1em" viewbox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"></path></svg></a></h1>
-<p>Arch is an intelligent proxy server designed agentic applications. <strong>Move faster</strong> by letting Arch handle the <strong>pesky heavy lifting</strong> in building agents:
-fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs.</p>
-<p>Past the thrill of an AI demo, have you found yourself hitting these walls? You know, the all too familiar ones:</p>
+<p>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:</p>
 <ul class="simple">
-<li><p>You break a prompt into specialized ones, but <strong>get stuck writing routing</strong> and handoff logic?</p></li>
-<li><p>You want use new LLMs, but <strong>struggle to quickly add LLMs</strong> without writing integration logic?</p></li>
-<li><p>You’re <strong>trapped in tedious prompting work</strong> to clarify inputs and user intents?</p></li>
-<li><p>You’re <strong>wasting cycles</strong> choosing and integrating <strong>code for observability</strong> instead of it just happening transparently?</p></li>
+<li><p>You want to build specialized agents, but get stuck writing <strong>routing and handoff</strong> code.</p></li>
+<li><p>You bogged down with prompt engineering work to <strong>clarify user intent and validate inputs</strong>.</p></li>
+<li><p>You want to <strong>quickly and safely use new LLMs</strong> but get stuck writing integration code.</p></li>
+<li><p>You waste cycles writing and maintaining <strong>observability</strong> code, when it can be transparent.</p></li>
+<li><p>You want to <strong>apply guardrails</strong>, but have to write custom code for each prompt and LLM.</p></li>
 </ul>
-<p>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!</p>
+<p>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.</p>
 <figure class="align-center" id="id2">
 <a class="reference internal image-reference" href="../_images/arch_network_diagram_high_level.png"><img alt="../_images/arch_network_diagram_high_level.png" src="../_images/arch_network_diagram_high_level.png" style="width: 100%;"/>
 </a>
@@ -174,7 +174,7 @@ fast input clarification, agent routing, seamless integration of prompts with to
 <p><span class="caption-text">High-level network flow of where Arch Gateway sits in your agentic stack. Designed for both ingress and egress prompt traffic.</span><a @click.prevent="window.navigator.clipboard.writeText($el.href); $el.setAttribute('data-tooltip', 'Copied!'); setTimeout(() =&gt; $el.setAttribute('data-tooltip', 'Copy link to this element'), 2000)" aria-label="Copy link to this element" class="headerlink" data-tooltip="Copy link to this element" href="#id2"><svg height="1em" viewbox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"></path></svg></a></p>
 </figcaption>
 </figure>
-<p><strong>Arch Gateway was built by the contributors of Envoy Proxy with the belief that:</strong></p>
+<p>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:</p>
 <blockquote>
 <div><p><em>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)
@@ -190,8 +190,8 @@ This gives Arch several advantages:</p>
 <li><p>Arch works with any application language. A single Arch deployment can act as gateway for AI applications written in Python, Java, C++, Go, Php, etc.</p></li>
 <li><p>Arch can be deployed and upgraded quickly across your infrastructure transparently without the horrid pain of deploying library upgrades in your applications.</p></li>
 </ul>
-<p><strong>Engineered with Fast LLMs:</strong> 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:</p>
+<p><strong>Engineered with Fast Task-Specific LLMs (TLMs):</strong> 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:</p>
 <ul class="simple">
 <li><p><strong>Function Calling:</strong> 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.
@@ -239,7 +239,7 @@ For more details, read <a class="reference internal" href="../guides/observabili
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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get_started/overview.html

@@ -157,9 +157,8 @@
 <div id="content" role="main">
 <section id="overview">
 <span id="id1"></span><h1>Overview<a @click.prevent="window.navigator.clipboard.writeText($el.href); $el.setAttribute('data-tooltip', 'Copied!'); setTimeout(() =&gt; $el.setAttribute('data-tooltip', 'Copy link to this element'), 2000)" aria-label="Copy link to this element" class="headerlink" data-tooltip="Copy link to this element" href="#overview"><svg height="1em" viewbox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"></path></svg></a></h1>
-<p>Welcome to Arch, The intelligent (edge and LLM) proxy server for agentic applications.</p>
-<p>Move <strong>faster</strong> by letting Arch handle the pesky heavy lifting in building agents: <strong>fast input clarification</strong>, <strong>agent routing</strong>,
-seamless integration of prompts with <strong>tools for common tasks</strong>, and <strong>unified access and observability of LLMs</strong>.</p>
+<p><a class="reference external" href="https://github.com/katanemo/arch" rel="nofollow noopener">Arch<svg fill="currentColor" height="1em" stroke="none" viewbox="0 96 960 960" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M188 868q-11-11-11-28t11-28l436-436H400q-17 0-28.5-11.5T360 336q0-17 11.5-28.5T400 296h320q17 0 28.5 11.5T760 336v320q0 17-11.5 28.5T720 696q-17 0-28.5-11.5T680 656V432L244 868q-11 11-28 11t-28-11Z"></path></svg></a> 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.</p>
+<p>Built by contributors to the widely adopted <a class="reference external" href="https://www.envoyproxy.io/" rel="nofollow noopener">Envoy Proxy<svg fill="currentColor" height="1em" stroke="none" viewbox="0 96 960 960" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M188 868q-11-11-11-28t11-28l436-436H400q-17 0-28.5-11.5T360 336q0-17 11.5-28.5T400 296h320q17 0 28.5 11.5T760 336v320q0 17-11.5 28.5T720 696q-17 0-28.5-11.5T680 656V432L244 868q-11 11-28 11t-28-11Z"></path></svg></a>, Arch helps you move faster by handling the pesky <em>low-level</em> 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.</p>
 <p>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.</p>
 <figure class="align-center" id="id2">
@@ -333,7 +332,7 @@ simplify the interaction with upstream LLMs, and improve observability all while
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get_started/quickstart.html

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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
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guides/agent_routing.html

@@ -291,7 +291,7 @@ please see our <a class="reference external" href="https://github.com/katanemo/a
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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guides/function_calling.html

@@ -367,7 +367,7 @@ on the stuff that matters most.</p>
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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guides/llm_router.html

@@ -157,7 +157,10 @@
 <div id="content" role="main">
 <section id="llm-routing">
 <span id="llm-router"></span><h1>LLM Routing<a @click.prevent="window.navigator.clipboard.writeText($el.href); $el.setAttribute('data-tooltip', 'Copied!'); setTimeout(() =&gt; $el.setAttribute('data-tooltip', 'Copy link to this element'), 2000)" aria-label="Copy link to this element" class="headerlink" data-tooltip="Copy link to this element" href="#llm-routing"><svg height="1em" viewbox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"></path></svg></a></h1>
-<p>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.</p>
+<p>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.</p>
+<p>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.</p>
+<p>This enables optimal performance, cost efficiency, and response quality by matching requests with the most suitable model from your available LLM fleet.</p>
 <section id="routing-workflow">
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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guides/observability/access_logging.html

@@ -243,7 +243,7 @@ Access logs can be exported to centralized logging systems (e.g., ELK stack or F
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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guides/observability/monitoring.html

@@ -255,7 +255,7 @@ are some sample configuration files for both, respectively.</p>
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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@@ -207,7 +207,7 @@
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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guides/observability/tracing.html

@@ -577,7 +577,7 @@ tools like AWS X-Ray and Datadog, enhancing observability and facilitating faste
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
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guides/prompt_guard.html

@@ -267,7 +267,7 @@ By implementing Prompt Guard, developers can provide a robust layer of input val
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
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index.html

@@ -151,10 +151,10 @@
 </a>
 <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&amp;utm_source=badge-top-post-badge&amp;utm_medium=badge&amp;utm_souce=badge-arch-3" target="_blank"><img alt="Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=565761&amp;theme=dark&amp;period=daily&amp;t=1742433071161" style="width: 250px; height: 54px;" width="250"/></a><p><a class="reference external" href="https://github.com/katanemo/arch" rel="nofollow noopener">Arch<svg fill="currentColor" height="1em" stroke="none" viewbox="0 96 960 960" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M188 868q-11-11-11-28t11-28l436-436H400q-17 0-28.5-11.5T360 336q0-17 11.5-28.5T400 296h320q17 0 28.5 11.5T760 336v320q0 17-11.5 28.5T720 696q-17 0-28.5-11.5T680 656V432L244 868q-11 11-28 11t-28-11Z"></path></svg></a> is an intelligent (edge and LLM) proxy, exclusively designed for prompts and agents - and built by the contributors of the widely adopted and loved <a class="reference external" href="https://www.envoyproxy.io/" rel="nofollow noopener">Envoy<svg fill="currentColor" height="1em" stroke="none" viewbox="0 96 960 960" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M188 868q-11-11-11-28t11-28l436-436H400q-17 0-28.5-11.5T360 336q0-17 11.5-28.5T400 296h320q17 0 28.5 11.5T760 336v320q0 17-11.5 28.5T720 696q-17 0-28.5-11.5T680 656V432L244 868q-11 11-28 11t-28-11Z"></path></svg></a> ).</p>
-<p><strong>Move faster</strong> by letting Arch handle the <strong>pesky heavy lifting</strong> 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.</p>
+<a href="https://www.producthunt.com/posts/arch-3?embed=true&amp;utm_source=badge-top-post-badge&amp;utm_medium=badge&amp;utm_souce=badge-arch-3" target="_blank"><img alt="Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=565761&amp;theme=dark&amp;period=daily&amp;t=1742433071161" style="width: 250px; height: 54px;" width="250"/></a><p><a class="reference external" href="https://github.com/katanemo/arch" rel="nofollow noopener">Arch<svg fill="currentColor" height="1em" stroke="none" viewbox="0 96 960 960" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M188 868q-11-11-11-28t11-28l436-436H400q-17 0-28.5-11.5T360 336q0-17 11.5-28.5T400 296h320q17 0 28.5 11.5T760 336v320q0 17-11.5 28.5T720 696q-17 0-28.5-11.5T680 656V432L244 868q-11 11-28 11t-28-11Z"></path></svg></a> 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.</p>
+<p>Built by contributors to the widely adopted <a class="reference external" href="https://www.envoyproxy.io/" rel="nofollow noopener">Envoy Proxy<svg fill="currentColor" height="1em" stroke="none" viewbox="0 96 960 960" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M188 868q-11-11-11-28t11-28l436-436H400q-17 0-28.5-11.5T360 336q0-17 11.5-28.5T400 296h320q17 0 28.5 11.5T760 336v320q0 17-11.5 28.5T720 696q-17 0-28.5-11.5T680 656V432L244 868q-11 11-28 11t-28-11Z"></path></svg></a>, Arch helps you move faster by handling the pesky <em>low-level</em> 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.</p>
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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-<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 14, 2025. </p>
+<p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc Last updated: Jun 17, 2025. </p>
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@@ -215,7 +215,7 @@
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-        <p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc&nbsp;Last updated: Jun 14, 2025.&nbsp;</p>
+        <p class="text-sm leading-loose text-center text-muted-foreground md:text-left">© 2025, Katanemo Labs, Inc&nbsp;Last updated: Jun 17, 2025.&nbsp;</p>
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