{"id":32699,"date":"2024-12-11T13:05:12","date_gmt":"2024-12-11T21:05:12","guid":{"rendered":"https:\/\/www.pugetsystems.com\/?post_type=case_study&#038;p=32699"},"modified":"2025-06-17T09:51:41","modified_gmt":"2025-06-17T16:51:41","slug":"vagents-the-power-of-the-machine-behind-llms","status":"publish","type":"case_study","link":"https:\/\/www.pugetsystems.com\/featured\/vagents-the-power-of-the-machine-behind-llms\/","title":{"rendered":"VAgents: The Power of the Machine Behind LLMs"},"content":{"rendered":"\n<div class=\"wp-block-cover full-width-no-gap\" style=\"min-height:361px;aspect-ratio:unset;\"><span aria-hidden=\"true\" class=\"wp-block-cover__background has-background-dim-0 has-background-dim has-background-gradient\" style=\"background:linear-gradient(135deg,rgb(0,0,0) 48%,rgba(155,81,224,0) 100%)\"><\/span><img loading=\"lazy\" decoding=\"async\" width=\"3840\" height=\"720\" class=\"wp-block-cover__image-background wp-image-32701\" alt=\"VAgents Case Study Banner\" src=\"https:\/\/wp-cdn.pugetsystems.com\/2024\/12\/VAgents-Banner.png\" data-object-fit=\"cover\"\/><div class=\"wp-block-cover__inner-container is-layout-flow wp-block-cover-is-layout-flow\"><div class=\"wp-bootstrap-blocks-container container mb-2 px-4\">\n\t\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:55%\">\n<h1 class=\"wp-block-heading has-text-align-left puget-header-shadow text-left has-white-color has-text-color has-link-color wp-elements-100e504afb11b535fe93a4ad9fc740f0\" id=\"h-vagents-the-power-of-the-machine-behind-llms\">VAgents: The Power of the Machine Behind LLMs<br><\/h1>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"has-text-align-left puget-header-shadow\"><strong>Training LLMs and AI agents requires a lot of processing power, so Brandon Bowsky and VAgents turned to Puget Systems for their development needs.<\/strong><\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-left is-layout-flex wp-container-core-buttons-is-layout-fdcfc74e wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button hs-cta-trigger-button hs-cta-trigger-button-187286957409\"><a class=\"wp-block-button__link has-black-color has-white-background-color has-text-color has-background wp-element-button\" href=\"#\"><strong>Download Case Study<\/strong><\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:45%\"><\/div>\n<\/div>\n\n<\/div>\n<\/div><\/div>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-text-align-center\" id=\"h-introducing-vagents\">Introducing VAgents<\/h2>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Brandon Bowsky is a consultant, business development professional, and serial entrepreneur. He is also the key person behind VAgents, a developer of AI-powered solutions that transform customer interactions by simplifying administrative processes, providing issue resolution from support content, and elevating experiences, all through the use of its signature AI agent technology.<\/p>\n\n\n<div class=\"wp-bootstrap-blocks-row row\">\n\t\n\n<div class=\"col-12 col-md-6\">\n\t\t\t\n\n<p><strong>VAgents is deeply rooted in arti\ufb01cial intelligence research and application, speci\ufb01cally in developing large language models (LLMs) and AI agents for various industries<\/strong>. As AI engineers, they see their role as spearheading the design, \ufb01ne-tuning, and deployment of these models. They oversee implementations across multiple sectors, including telephony, sales, customer service, and debt collections, with the goal being to leverage AI to automate processes, enhance customer interactions, and generate business value.<\/p>\n\n\n\n<p>VAgents have become a hub of computational creativity, which is why the team turned to Puget Systems to ensure they can work with the latest and most complex AI models. We recently spoke with Brandon who shared some of his perspectives and experience working with LLMs, and the role of specialized computing in the execution of their work.<\/p>\n\n\t<\/div>\n\n\n\n<div class=\"col-12 col-md-6\">\n\t\t\t\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"497\" height=\"330\" src=\"https:\/\/wp-cdn.pugetsystems.com\/2024\/12\/VAgents-Featured-Image-e1733945203771.jpg\" alt=\"Introducing VAgents - A First-Of-Its-Kind Outbound Sales &amp; Virtual Support Agent\" class=\"wp-image-32704\"\/><\/figure>\n\n\t<\/div>\n\n<\/div>\n\n\n\n<p>\u201cWe specialize in generating consumer demand in numerous verticals and converting that demand into high-intent calls and leads that power industry leaders in direct-to-consumer sales. With a team of veteran experts in a number of fields, our core tenets include ensuring the best customer experience, educating our clients and affiliates, conducting good and compliant business, and prioritizing our integrity and reputation before and above dollar signs.\u201d<\/p>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-text-align-center\" id=\"h-how-vagents-uses-large-language-models\">How VAgents Uses Large Language Models<\/h2>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>LLMs play an important role in VAgents\u2019 daily tasks and operations and touch many aspects of the business. Currently, VAgents are using large language models for several applications, including:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Conversational AI in telephony and sales<\/strong>: Building agents that can handle inbound and outbound customer interactions, offering personalized recommendations and lead quali\ufb01cation.<\/li>\n\n\n\n<li><strong>Customer service automation<\/strong>: Developing AI agents that can autonomously handle common inquiries, provide tier-1 support, and escalate complex cases as needed.<\/li>\n\n\n\n<li><strong>Debt collection AI<\/strong>: Creating polite yet firm agents to handle early-stage debt collections, with a focus on compliance and empathy.<\/li>\n\n\n\n<li><strong>Real-time data analysis and sentiment detection<\/strong>: Enabling agents to gauge customer sentiment during interactions and adjust their tone accordingly.<\/li>\n<\/ul>\n\n\n\n<p>Prior to integrating their new servers from Puget Systems, they were facing a number of challenges, such as:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Limited computational resources<\/strong>: Training LLMs required immense GPU power, and their prior infrastructure could not handle the load efficiently.<\/li>\n\n\n\n<li><strong>Slow training times<\/strong>: Due to resource constraints, training models took an excessive amount of time, delaying project milestones.<\/li>\n\n\n\n<li><strong>Scalability issues<\/strong>: As their projects grew in complexity, the old infrastructure couldn\u2019t scale to handle larger datasets or more demanding AI architectures.<\/li>\n<\/ul>\n\n\n\n<p>Brandon continued, \u201cWe were constantly spinning up new environments trying to replicate an on-prem scenario, but we were using a bunch of external services for GPUs. But the time it takes to get everything set up and ready, you can\u2019t truly tell if it\u2019s a viable solution for on-prem, especially when you\u2019re trying to determine if it\u2019s viable at scale. We discovered that iterating and testing systems in-house was significantly more efficient. That\u2019s when we started looking.\u201d<\/p>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-text-align-center\" id=\"h-enter-puget-systems\">Enter Puget Systems<\/h2>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>\u201cWe came across Puget Systems through peer recommendations within the AI research community. Given the positive feedback and your focus on custom hardware configurations for machine learning, <strong>we knew your solution would meet our growing needs<\/strong>.\u201d<\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-cover is-light full-width\" style=\"min-height:50px;aspect-ratio:unset;\"><span aria-hidden=\"true\" class=\"wp-block-cover__background has-background-dim-100 has-background-dim\" style=\"background-color:#f2f2f2\"><\/span><div class=\"wp-block-cover__inner-container is-layout-flow wp-block-cover-is-layout-flow\"><div class=\"wp-bootstrap-blocks-container container mb-0\">\n\t\n<blockquote class=\"puget-blockquote blockquote-gray\">\n    <div class=\"blockquote-text\">\n\t    <p><em>\u201cWe came across Puget Systems through peer recommendations within the AI research community. Given the positive feedback and your focus on custom hardware con\ufb01gurations for machine learning, we knew your solution would meet our growing needs.\u201d<\/em><\/p>\n    <\/div>\n                <cite>Brandon Bowsky<\/cite>\n        <\/blockquote>\n\n<\/div>\n<\/div><\/div>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Several factors led Brandon to choose Puget Systems, which according to his team are essential for training, fine-tuning and running inference with large language models. The factors included:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Optimized hardware<\/strong>: The inclusion of 4x NVIDIA RTX\u2122 6000 Ada Generation GPUs was a major selling point, allowing them to handle large-scale AI tasks efficiently. <\/li>\n\n\n\n<li><strong>Powerful CPU and RAM<\/strong>: To support quad GPUs and minimize bottlenecks, an Intel Xeon\u2122 w9-3495X with support for 112 PCIe lanes was selected as the CPU. It provided the necessary computing muscle and memory stability for training and deploying large models.<\/li>\n\n\n\n<li><strong>Scalability<\/strong>: They needed a system that could scale with their increasing demands, and Puget Systems&#8217; solution offered exactly what they were looking for.<\/li>\n\n\n\n<li><strong>Strong reputation in AI<\/strong>: Puget\u2019s track record for delivering high-performance systems tailored to machine learning work\ufb02ows was a key differentiator.<\/li>\n<\/ul>\n\n\n\n<p>\u201cThe implementation process was straightforward. Once the server arrived, we were able to integrate it into our AI development environment quickly. Our familiarity with machine learning pipelines meant we faced no major challenges in setup.\u201d<\/p>\n\n\n\n<p>We asked Brandon how the server\u2019s performance was measuring up to expectations in terms of speed, reliability, and scalability. Brandon replied, \u201cThe server\u2019s performance has exceeded our expectations in several ways. Regarding speed; <strong>training times have been cut by over 60%, allowing for quicker model iterations<\/strong>. On reliability, the system has been stable even under heavy loads, with no performance dips. As far as scalability is concerned, we\u2019ve been able to scale our AI projects signi\ufb01cantly, training models that were previously impossible due to resource constraints.\u201d<\/p>\n\n\n\n<p>\u201cAnd all of this has dramatically improved our workflow. We can now train and deploy larger, more complex models much faster. This has enabled us to experiment with more ambitious architectures and \ufb01ne-tune models in ways we previously couldn\u2019t.\u201d<\/p>\n\n\n\n<p>Brandon elaborated on the performance improvements: \u201cTraining time has been reduced by approximately 65%, which has led to faster project completion and quicker deployment cycles. Cost reductions are significant; the ability to train models in-house has reduced the need for costly cloud computing services. And regarding inference speed, our real-time interactions, such as <strong>customer service responses, are now 40% faster<\/strong>, improving user experience.\u201d<\/p>\n\n\n\n<p>\u201cOne unexpected bene\ufb01t, however,&nbsp; has been the ability to explore multi-modal AI models\u2014something we hadn\u2019t considered before due to hardware limitations. Additionally, the system\u2019s power has allowed us to handle larger datasets and perform more extensive model evaluations.\u201d<\/p>\n\n\n\n<p>\u201c<strong>The server has been transformative for our AI development efforts<\/strong>. It has allowed us to take on more ambitious projects and deliver better results in less time. Your solution is a game-changer.\u201d<\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-cover full-width\" style=\"min-height:50px;aspect-ratio:unset;\"><span aria-hidden=\"true\" class=\"wp-block-cover__background has-background-dim-100 has-background-dim\" style=\"background-color:#163ad6\"><\/span><div class=\"wp-block-cover__inner-container is-layout-flow wp-block-cover-is-layout-flow\"><div class=\"wp-bootstrap-blocks-container container mb-0\">\n\t\n<blockquote class=\"puget-blockquote blockquote-blue\">\n    <div class=\"blockquote-text\">\n\t    <p><em>&#8220;The server has been transformative for our AI development efforts. It has allowed us to take on more ambitious projects and deliver better results in less time. Your solution is a game-changer.&#8221;<\/em><\/p>\n    <\/div>\n                <cite>Brandon Bowsky<\/cite>\n        <\/blockquote>\n\n<\/div>\n<\/div><\/div>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:60%\">\n<h2 class=\"wp-block-heading has-text-align-center text-md-left\" id=\"h-system-specifications\">System Specifications<\/h2>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>VAgents has been developed on a Puget Rackstation X140-5U:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>ASUS Pro WS W790E-SAGE SE<\/li>\n\n\n\n<li>Intel Xeon\u2122 w9-3495X 56-Core Processor<\/li>\n\n\n\n<li>512GB DDR5-4800 (8 x 64GB)<\/li>\n\n\n\n<li>4 x NVIDIA RTX\u2122 6000 Ada Generation 48GB<\/li>\n\n\n\n<li>2 x 4TB M.2 NMVe SSDs<\/li>\n\n\n\n<li>SilverStone RM51 5U Chassis<\/li>\n\n\n\n<li>Dual Power Supplies (1300W + 750W)<\/li>\n\n\n\n<li>Ubuntu 22.04 LTS Server<\/li>\n<\/ul>\n\n\n\n<p>To learn more about VAgents and their groundbreaking work in LLMs and AI agents, please <a href=\"https:\/\/vagents.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">visit their website here<\/a>.<\/p>\n\n\n\n<p>For more information on Puget Systems and our AI solutions, check out <a href=\"https:\/\/www.pugetsystems.com\/solutions\/ai-and-hpc-workstations\/ai-large-language-models\/\">our Recommended Systems for Large Language Models<\/a>.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:40%\">\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2334\" height=\"2560\" src=\"https:\/\/wp-cdn.pugetsystems.com\/2024\/12\/Rackstation-Interior-Cropped-scaled.jpg\" alt=\"Puget Rackstation X140-5U Interior with Four NVIDIA RTX 6000 Ada Generation GPUs\" class=\"wp-image-32702\" style=\"object-fit:cover\"\/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-text-align-center\" id=\"h-talk-to-an-expert\">Talk to an Expert<\/h2>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"has-text-align-left\">We specialize in building computer systems tailored for each of our customers \u2013 whether workstations, servers, storage solutions, or a combination of them all! We have found that the most effective way to ensure we meet your specific requirements is through direct communication. Our team of expert, non-commissioned consultants is adept at configuring systems that align precisely with your needs. They can refine a quote you\u2019ve already saved or help you navigate our offerings by understanding your use case and workflow \u2013 all with no cost or obligation! 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