{"id":5345,"date":"2026-03-20T11:53:55","date_gmt":"2026-03-20T06:23:55","guid":{"rendered":"https:\/\/newfangled.io\/blog\/?p=5345"},"modified":"2026-03-20T11:53:55","modified_gmt":"2026-03-20T06:23:55","slug":"llm-infrastructure-cost-enterprise-breakdown-strategic-comparison","status":"publish","type":"post","link":"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/","title":{"rendered":"LLM Infrastructure Cost: Enterprise Breakdown &#038; Strategic Comparison"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_51_1 counter-hierarchy ez-toc-counter ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title ez-toc-toggle\" style=\"cursor: pointer\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#LLM_Infrastructure_Cost_Enterprise_AI_breakdown_Strategic_Comparison\" title=\"LLM Infrastructure Cost: Enterprise AI breakdown &amp; Strategic Comparison\">LLM Infrastructure Cost: Enterprise AI breakdown &amp; Strategic Comparison<\/a><ul class='ez-toc-list-level-2'><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#Introduction_Rethinking_LLM_Infrastructure_Cost\" title=\"Introduction: Rethinking LLM Infrastructure Cost\">Introduction: Rethinking LLM Infrastructure Cost<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#The_Hidden_Reality_of_the_LLM_Infrastructure_Cost\" title=\"The Hidden Reality of the LLM Infrastructure Cost\">The Hidden Reality of the LLM Infrastructure Cost<\/a><ul class='ez-toc-list-level-3'><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#Why_the_LLM_Infrastructure_Cost_Is_Misunderstood\" title=\"Why the LLM Infrastructure Cost Is Misunderstood\">Why the LLM Infrastructure Cost Is Misunderstood<\/a><ul class='ez-toc-list-level-4'><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#1_Over-Focus_on_Compute\" title=\"1. Over-Focus on Compute\">1. Over-Focus on Compute<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#2_Ignoring_Lifecycle_Costs\" title=\"2. Ignoring Lifecycle Costs\">2. Ignoring Lifecycle Costs<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#3_Treating_LLMs_as_APIs_Instead_of_Systems\" title=\"3. Treating LLMs as APIs Instead of Systems\">3. Treating LLMs as APIs Instead of Systems<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#The_5-Layer_for_LLM_Infrastructure_Cost\" title=\"The 5-Layer for LLM Infrastructure Cost\">The 5-Layer for LLM Infrastructure Cost<\/a><ul class='ez-toc-list-level-3'><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#1_Compute_Layer_The_Engine\" title=\"1. Compute Layer (The Engine)\">1. Compute Layer (The Engine)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#2_Data_Layer_The_Fuel\" title=\"2. Data Layer (The Fuel)\">2. Data Layer (The Fuel)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#3_Orchestration_Layer_The_Coordinator\" title=\"3. Orchestration Layer (The Coordinator)\">3. Orchestration Layer (The Coordinator)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#4_Reliability_Layer_The_Safety_Net\" title=\"4. Reliability Layer (The Safety Net)\">4. Reliability Layer (The Safety Net)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#5_Governance_Layer_The_Control_System\" title=\"5. Governance Layer (The Control System)\">5. Governance Layer (The Control System)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#Key_Insight\" title=\"Key Insight\">Key Insight<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#Understanding_LLM_Infrastructure_Where_the_Cost_Comes_From\" title=\"Understanding LLM Infrastructure: Where the Cost Comes From\">Understanding LLM Infrastructure: Where the Cost Comes From<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#Understanding_VADY_A_Purpose-Built_Alternative\" title=\"Understanding VADY: A Purpose-Built Alternative\">Understanding VADY: A Purpose-Built Alternative<\/a><ul class='ez-toc-list-level-3'><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#Where_VADY_Reduces_System_Complexity\" title=\"Where VADY Reduces System Complexity\">Where VADY Reduces System Complexity<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#LLM_Infrastructure_Cost_vs_VADY_Infrastructure\" title=\"LLM Infrastructure Cost vs VADY Infrastructure\">LLM Infrastructure Cost vs VADY Infrastructure<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#Conclusion\" title=\"Conclusion\">Conclusion<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"LLM_Infrastructure_Cost_Enterprise_AI_breakdown_Strategic_Comparison\"><\/span>LLM Infrastructure Cost: Enterprise AI breakdown &amp; Strategic Comparison<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<h2><span class=\"ez-toc-section\" id=\"Introduction_Rethinking_LLM_Infrastructure_Cost\"><\/span>Introduction: Rethinking LLM Infrastructure Cost<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Most enterprises assume the cost of running LLM infrastructure is primarily driven by GPUs and model inference. That assumption is incomplete. In production environments, the LLM Infrastructure Cost is shaped by an entire system: data pipelines, orchestration layers, reliability mechanisms, and governance controls. Each of these layers introduces its own operational overhead, and more importantly, they compound as usage scales. What begins as a straightforward model deployment quickly evolves into a multi-layered system that requires continuous management, tuning, and monitoring.<\/p>\n<p>&nbsp;<\/p>\n<p>As <a href=\"https:\/\/newfangled.io\/\">NewFangled Vision<\/a> observed, a consistent pattern emerges: organizations plan for model costs but end up paying for system complexity. Early estimates focus on tokens and compute, while the real expenses surface later in integration, data movement, and compliance requirements. Understanding this shift from model-centric thinking to system-level cost awareness is essential for enterprises aiming to build scalable and economically viable AI solutions.<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_5352\" aria-describedby=\"caption-attachment-5352\" style=\"width: 1920px\" class=\"wp-caption alignnone\"><img decoding=\"async\" class=\"wp-image-5352 size-full\" src=\"https:\/\/newfangled.io\/blog\/wp-content\/uploads\/2026\/03\/VADY-blog-16.jpg\" alt=\"Comparison of LLM infrastructure cost and VADY showing layered complexity vs simplified architecture and cost.\" width=\"1920\" height=\"1080\" \/><figcaption id=\"caption-attachment-5352\" class=\"wp-caption-text\">LLM vs <a href=\"https:\/\/www.linkedin.com\/company\/nf-vision\/posts\/?feedView=all\" target=\"_blank\" rel=\"noopener\">VADY<\/a>(<a href=\"https:\/\/newfangled.io\/\">NewFangled Vision<\/a>) : How system complexity impacts LLM infrastructure cost.<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Hidden_Reality_of_the_LLM_Infrastructure_Cost\"><\/span>The Hidden Reality of the LLM Infrastructure Cost<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Before diving into architecture, it is important to ground the discussion in a few practical realities that shape the LLM Infrastructure Cost in enterprise environments:<\/p>\n<ul>\n<li><span style=\"color: #000000;\">Most enterprises underestimate the cost of running LLM infrastructure by 3\u20135x<\/span><\/li>\n<li><span style=\"color: #000000;\">Compute often represents less than half of the total operational cost<\/span><\/li>\n<li><span style=\"color: #000000;\">Costs increase rapidly as systems transition from pilot to production scale<\/span><\/li>\n<\/ul>\n<p>These patterns are consistent across industries and use cases. What appears manageable during initial experimentation becomes significantly more complex once the system is exposed to real workloads, users, and enterprise constraints.<\/p>\n<p>&nbsp;<\/p>\n<p>In simple terms, running an LLM is not expensive because of a single component it becomes expensive because every supporting layer grows with scale. Data pipelines expand, orchestration becomes more intricate, and governance requirements intensify.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Why_the_LLM_Infrastructure_Cost_Is_Misunderstood\"><\/span><b>Why the LLM Infrastructure Cost Is Misunderstood<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">A major reason enterprises miscalculate LLM infrastructure cost is rooted in how they frame the problem. Instead of evaluating the system holistically, they focus on isolated components or simplified assumptions. Three patterns consistently emerge:<\/span><\/p>\n<p>&nbsp;<\/p>\n<h4><span class=\"ez-toc-section\" id=\"1_Over-Focus_on_Compute\"><\/span><strong>1. Over-Focus on Compute<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Teams tend to focus on GPU pricing and inference cost because these are easy to measure and benchmark.<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">GPU usage and token-based pricing are visible and quantifiable<\/span><\/li>\n<li><span style=\"color: #000000;\">Cost calculators and vendor estimates reinforce this focus<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">However, compute is merely the most obvious aspect of the system and not the most important. As deployments scale, other layers begin to dominate overall costs.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h4><span class=\"ez-toc-section\" id=\"2_Ignoring_Lifecycle_Costs\"><\/span><strong>2. Ignoring Lifecycle Costs<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">LLM systems are not static; to remain successful, they must be maintained on a constant basis.<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">Updating and cleaning data sources<\/span><\/li>\n<li><span style=\"color: #000000;\">Rebuilding embeddings and indexes<\/span><\/li>\n<li><span style=\"color: #000000;\">Refining prompts and workflows<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">These ongoing activities introduce recurring operational costs that are often excluded from initial planning. Over time, lifecycle costs can exceed the original infrastructure investment.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h4><span class=\"ez-toc-section\" id=\"3_Treating_LLMs_as_APIs_Instead_of_Systems\"><\/span><strong>3. Treating LLMs as APIs Instead of Systems<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Many organizations begin with a simplified assumption: <strong><em>\u201cWe\u2019ll integrate an LLM API.\u201d<\/em><\/strong><\/span><\/p>\n<p><span style=\"font-weight: 400;\">In practice, they end up building:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">A distributed AI system<\/span><\/li>\n<li><span style=\"color: #000000;\">Multiple interdependent services<\/span><\/li>\n<li><span style=\"color: #000000;\">Several points of failure and monitoring requirements<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">The change from API integration to system design considerably raises the LLM Infrastructure Cost, both in terms of engineering effort and operational overhead.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_5-Layer_for_LLM_Infrastructure_Cost\"><\/span><b>The 5-Layer for LLM Infrastructure Cost<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">To accurately understand LLM infrastructure Cost breakdown, it is helpful to divide it into layered systems. Consider this a stack: each layer increases capability but also introducing its own cost, dependencies, and operational complexity. As systems scale, these layers do not increase independently; instead, they compound, resulting in a nonlinear overall cost.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"1_Compute_Layer_The_Engine\"><\/span><strong>1. Compute Layer (The Engine)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Includes<\/strong>:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">GPUs or inference engines<\/span><\/li>\n<li><span style=\"color: #000000;\">Real-time and batch processing<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Simple view<\/strong>: <\/span><span style=\"font-weight: 400;\">This is the core engine that powers the model\u2019s ability to generate responses.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Reality<\/strong>:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Compute is often over-provisioned due to unpredictable demand patterns. Enterprises tend to allocate for peak usage, which leads to underutilized resources during normal operation. While compute is the most visible cost component, it is also one of the easier layers to optimize compared to others.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"2_Data_Layer_The_Fuel\"><\/span><strong>2. Data Layer (The Fuel)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Includes<\/strong>:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">Embeddings<\/span><\/li>\n<li><span style=\"color: #000000;\">Vector databases<\/span><\/li>\n<li><span style=\"color: #000000;\">Data ingestion pipelines<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><strong>Simple view: <\/strong><span style=\"font-weight: 400;\">This layer feeds the model with relevant context and knowledge.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Reality<\/strong>:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Data is not static. It requires continuous updating, cleaning, indexing, and reprocessing. As data volumes grow, so do storage, compute, and pipeline costs. In many enterprise deployments, the data layer becomes a long-term cost driver, especially in systems relying on retrieval-augmented generation (RAG).<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"3_Orchestration_Layer_The_Coordinator\"><\/span><strong>3. Orchestration Layer (The Coordinator)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Includes<\/strong>:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">Prompt routing<\/span><\/li>\n<li><span style=\"color: #000000;\">Workflow logic<\/span><\/li>\n<li><span style=\"color: #000000;\">Multi-model handling<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Simple view<\/strong>: <\/span><span style=\"font-weight: 400;\">This layer connects all components and ensures the system behaves as expected.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><strong>Reality:<\/strong><\/p>\n<p><span style=\"font-weight: 400;\">As use cases expand, orchestration becomes increasingly complex. Simple pipelines evolve into multi-step workflows involving multiple models, tools, and data sources. Maintaining and debugging these workflows requires specialized engineering effort, making this layer a significant contributor to operational cost.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"4_Reliability_Layer_The_Safety_Net\"><\/span><strong>4. Reliability Layer (The Safety Net)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Includes<\/strong>:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">Monitoring<\/span><\/li>\n<li><span style=\"color: #000000;\">Output validation<\/span><\/li>\n<li><span style=\"color: #000000;\">Fallback systems<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><strong>Simple view:\u00a0<\/strong><span style=\"font-weight: 400;\">This ensures the system performs consistently and reliably.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Reality<\/strong>:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Enterprise environments require great dependability. This entails creating systems that identify problems, validate outputs, and recover gracefully. These capabilities necessitate more infrastructure, tooling, and engineering investment. While reliability is sometimes disregarded in the early phases, it becomes critical and costly as scale increases.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"5_Governance_Layer_The_Control_System\"><\/span><strong>5. Governance Layer (The Control System)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Includes<\/strong>:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">Security and access control<\/span><\/li>\n<li><span style=\"color: #000000;\">Compliance mechanisms<\/span><\/li>\n<li><span style=\"color: #000000;\">Data protection<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><strong>Simple view: <\/strong><span style=\"font-weight: 400;\">This layer ensures the system is secure, compliant, and trustworthy.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><strong>Reality<\/strong>:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Governance requirements in enterprises are stringent. Implementing access controls, audit trails, and compliance mechanisms often leads to duplication of infrastructure and added system complexity. In regulated industries, this layer can significantly increase both cost and deployment timelines.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Key_Insight\"><\/span><b>Key Insight<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">The LLM Infrastructure Cost does not scale linearly. Each layer depends on and amplifies the others:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">More data increases orchestration complexity<\/span><\/li>\n<li><span style=\"color: #000000;\">More orchestration requires stronger reliability systems<\/span><\/li>\n<li><span style=\"color: #000000;\">More reliability introduces additional governance needs<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">As a result, what starts as a manageable system can quickly evolve into a complex, multi-layered architecture where costs grow faster than expected.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Understanding this layered model is essential for designing systems that are not only functional, but also economically sustainable.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Understanding_LLM_Infrastructure_Where_the_Cost_Comes_From\"><\/span><b>Understanding LLM Infrastructure: Where the Cost Comes From<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">LLM infrastructure is designed to deliver high flexibility and advanced reasoning capabilities, making it suitable for complex and evolving enterprise use cases. Unlike traditional systems, it is not limited to predefined rules and can adapt to a wide range of inputs and scenarios.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">It excels at:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">Understanding large volumes of unstructured data such as documents, emails, and reports<\/span><\/li>\n<li><span style=\"color: #000000;\">Generating human-like responses that feel natural and contextual<\/span><\/li>\n<li><span style=\"color: #000000;\">Handling open-ended queries where the expected output is not strictly defined<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">This makes LLM systems particularly useful for knowledge assistants, research workflows, and decision-support applications.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">However, this flexibility introduces additional cost and complexity across the system:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">High compute demand due to large model sizes and inference requirements<\/span><\/li>\n<li><span style=\"color: #000000;\">Complex data pipelines, especially in architectures like retrieval-augmented generation (RAG)<\/span><\/li>\n<li><span style=\"color: #000000;\">Dynamic orchestration logic to manage prompts, workflows, and multi-step reasoning<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Increased governance requirements to manage risks such as hallucinations, data leakage, and compliance<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">In simple terms:<\/span><\/p>\n<blockquote><p><i><span style=\"font-weight: 400;\">LLM systems trade higher cost for greater intelligence and flexibility.<\/span><\/i><\/p><\/blockquote>\n<p><span style=\"font-weight: 400;\">As capability increases, so does the need for supporting infrastructure, making the overall system more resource-intensive and operationally complex.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Understanding_VADY_A_Purpose-Built_Alternative\"><\/span><b>Understanding <a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">VADY<\/a>: A Purpose-Built Alternative<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">At <a href=\"https:\/\/newfangled.io\/\">NewFangled Vision<\/a>, <a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">VADY<\/a> represents a fundamentally different approach to enterprise AI one that prioritizes decision-making over open-ended generation. Instead of focusing on broad reasoning capabilities, <a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">VADY<\/a> is designed to deliver structured, reliable, and actionable outcomes within business environments.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">VADY<\/a> is a decision intelligence platform built to work with:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">Structured and semi-structured enterprise data such as ERP, CRM, and operational systems<\/span><\/li>\n<li><span style=\"color: #000000;\">Defined business workflows and rules<\/span><\/li>\n<li><span style=\"color: #000000;\">Real-time insights and actionable recommendations<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">This makes it particularly effective for operational use cases where consistency and accuracy are critical.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Unlike LLM-based systems, <a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">VADY<\/a> is engineered with a different set of priorities:<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">It does not rely heavily on large-scale model inference<\/span><\/li>\n<li><span style=\"color: #000000;\">It focuses on deterministic and predictable outputs<\/span><\/li>\n<li><span style=\"color: #000000;\">It is optimized for enterprise efficiency, stability, and cost control<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Because of this design, <a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">VADY<\/a> reduces the need for complex supporting layers such as heavy data pipelines or dynamic orchestration.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">In simple terms:<\/span><\/p>\n<blockquote><p><i><span style=\"font-weight: 400;\"><a href=\"https:\/\/newfangled.io\/\">VADY<\/a> trades flexibility for efficiency, predictability, and lower cost.<\/span><\/i><\/p><\/blockquote>\n<p><span style=\"font-weight: 400;\">This makes it well-suited for organizations that require dependable, repeatable outcomes without the overhead associated with highly flexible AI systems.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Where_VADY_Reduces_System_Complexity\"><\/span><b>Where <a href=\"https:\/\/newfangled.io\/\">VADY<\/a> Reduces System Complexity<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Compared to LLM systems, <a href=\"https:\/\/newfangled.io\/\">VADY<\/a> simplifies several layers of the overall architecture, which directly impacts the cost of deployment and operations. Instead of managing a highly dynamic and complex system, enterprises can work with a more structured and predictable setup.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.linkedin.com\/company\/nf-vision\/posts\/?feedView=all\" target=\"_blank\" rel=\"noopener\">VADY<\/a> reduces complexity in the following ways:<\/span><\/p>\n<ul>\n<li><strong style=\"color: #000000;\">No heavy embedding pipelines in most cases : <\/strong><span style=\"font-weight: 400;\">Eliminates the need for continuous data transformation, indexing, and reprocessing typically required in LLM-based systems<\/span><\/li>\n<li><strong style=\"color: #000000;\">Reduced need for complex orchestration : <\/strong><span style=\"font-weight: 400;\">Workflows are more structured, minimizing the need for multi-step prompt chaining and model coordination<\/span><\/li>\n<li><strong style=\"color: #000000;\">More predictable outputs \u2192 less validation overhead : <\/strong><span style=\"font-weight: 400;\">Controlled responses reduce the need for extensive output checking, monitoring, and fallback mechanisms<\/span><\/li>\n<li><strong style=\"color: #000000;\">Lower governance complexity due to controlled responses : <\/strong><span style=\"font-weight: 400;\">With reduced variability, security, compliance, and access control become easier to manage<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Because of these simplifications, <a href=\"https:\/\/www.linkedin.com\/company\/nf-vision\/posts\/?feedView=all\" target=\"_blank\" rel=\"noopener\">VADY<\/a> avoids many of the compounding costs seen in LLM architectures. This results in a system that is easier to maintain, requires less engineering overhead, and delivers a more stable and predictable cost structure for enterprise use cases.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"LLM_Infrastructure_Cost_vs_VADY_Infrastructure\"><\/span><strong>LLM Infrastructure Cost vs <a href=\"https:\/\/www.linkedin.com\/company\/nf-vision\/posts\/?feedView=all\" target=\"_blank\" rel=\"noopener\">VADY<\/a> Infrastructure<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<table>\n<tbody>\n<tr>\n<td><b>Dimension<\/b><\/td>\n<td><b>LLM Infrastructure<\/b><\/td>\n<td><b><a href=\"https:\/\/www.linkedin.com\/company\/nf-vision\/posts\/?feedView=all\" target=\"_blank\" rel=\"noopener\">VADY<\/a> (<a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">NewFangled Vision<\/a>)<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Core Purpose<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Reasoning &amp; generation<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Decision intelligence<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Data Type<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Unstructured heavy<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Structured, Unstructured &amp; enterprise data<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Compute Cost<\/span><\/td>\n<td><span style=\"font-weight: 400;\">High (GPU-intensive)<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Lower (optimized processing)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Output Style<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Open-ended<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Controlled &amp; actionable<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">System Complexity<\/span><\/td>\n<td><span style=\"font-weight: 400;\">High<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Moderate<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Cost Behavior<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Non-linear scaling<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Predictable scaling<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Governance Needs<\/span><\/td>\n<td><span style=\"font-weight: 400;\">High<\/span><\/td>\n<td><span style=\"font-weight: 400;\">More manageable<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Best Use Cases<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Knowledge, reasoning<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Business decisions, workflows<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><strong>Conclusion<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">The LLM Infrastructure Cost is not just a pricing question\u2014it is fundamentally an architectural outcome. Looking only at model or compute costs creates a narrow view that often leads to miscalculations as systems scale.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">In real-world deployments, cost emerges from how different layers of the system interact, including data pipelines, orchestration logic, reliability mechanisms, and governance requirements. As these layers grow and become more interconnected, complexity increases, and with it, the overall operational cost.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Enterprises that focus only on model-level expenses often encounter unexpected challenges in production. In contrast, those that understand cost as a system-level outcome are better equipped to design efficient and sustainable AI solutions.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">At <a href=\"https:\/\/www.youtube.com\/@NewFangledVADY\" target=\"_blank\" rel=\"noopener\">NewFangled Vision<\/a>, this shift is clear: the future of enterprise AI is not about choosing the most advanced models, it is about designing the right systems that balance performance, control, and cost.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p>;<\/p>\n<div class=\"pvc_clear\"><\/div>\n<p id=\"pvc_stats_5345\" class=\"pvc_stats total_only  \" data-element-id=\"5345\" style=\"\"><i class=\"pvc-stats-icon medium\" aria-hidden=\"true\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"far\" data-icon=\"chart-bar\" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\" class=\"svg-inline--fa fa-chart-bar fa-w-16 fa-2x\"><path fill=\"currentColor\" d=\"M396.8 352h22.4c6.4 0 12.8-6.4 12.8-12.8V108.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v230.4c0 6.4 6.4 12.8 12.8 12.8zm-192 0h22.4c6.4 0 12.8-6.4 12.8-12.8V140.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v198.4c0 6.4 6.4 12.8 12.8 12.8zm96 0h22.4c6.4 0 12.8-6.4 12.8-12.8V204.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v134.4c0 6.4 6.4 12.8 12.8 12.8zM496 400H48V80c0-8.84-7.16-16-16-16H16C7.16 64 0 71.16 0 80v336c0 17.67 14.33 32 32 32h464c8.84 0 16-7.16 16-16v-16c0-8.84-7.16-16-16-16zm-387.2-48h22.4c6.4 0 12.8-6.4 12.8-12.8v-70.4c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v70.4c0 6.4 6.4 12.8 12.8 12.8z\" class=\"\"><\/path><\/svg><\/i> <img decoding=\"async\" width=\"16\" height=\"16\" alt=\"Loading\" src=\"https:\/\/newfangled.io\/blog\/wp-content\/plugins\/page-views-count\/ajax-loader-2x.gif\" border=0 \/><\/p>\n<div class=\"pvc_clear\"><\/div>\n","protected":false},"excerpt":{"rendered":"<p>LLM Infrastructure Cost: Enterprise AI breakdown &amp; Strategic Comparison Introduction: Rethinking LLM Infrastructure Cost Most enterprises assume the cost of running LLM infrastructure is primarily driven by GPUs and model inference. That assumption is incomplete. In production environments, the LLM Infrastructure Cost is shaped by an entire system: data pipelines, orchestration layers, reliability mechanisms, and [&hellip;]<\/p>\n<div class=\"pvc_clear\"><\/div>\n<p id=\"pvc_stats_5345\" class=\"pvc_stats total_only  \" data-element-id=\"5345\" style=\"\"><i class=\"pvc-stats-icon medium\" aria-hidden=\"true\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"far\" data-icon=\"chart-bar\" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\" class=\"svg-inline--fa fa-chart-bar fa-w-16 fa-2x\"><path fill=\"currentColor\" d=\"M396.8 352h22.4c6.4 0 12.8-6.4 12.8-12.8V108.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v230.4c0 6.4 6.4 12.8 12.8 12.8zm-192 0h22.4c6.4 0 12.8-6.4 12.8-12.8V140.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v198.4c0 6.4 6.4 12.8 12.8 12.8zm96 0h22.4c6.4 0 12.8-6.4 12.8-12.8V204.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v134.4c0 6.4 6.4 12.8 12.8 12.8zM496 400H48V80c0-8.84-7.16-16-16-16H16C7.16 64 0 71.16 0 80v336c0 17.67 14.33 32 32 32h464c8.84 0 16-7.16 16-16v-16c0-8.84-7.16-16-16-16zm-387.2-48h22.4c6.4 0 12.8-6.4 12.8-12.8v-70.4c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v70.4c0 6.4 6.4 12.8 12.8 12.8z\" class=\"\"><\/path><\/svg><\/i> <img decoding=\"async\" width=\"16\" height=\"16\" alt=\"Loading\" src=\"https:\/\/newfangled.io\/blog\/wp-content\/plugins\/page-views-count\/ajax-loader-2x.gif\" border=0 \/><\/p>\n<div class=\"pvc_clear\"><\/div>\n","protected":false},"author":10,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[151,181,178,137,142],"tags":[180,133,194,138,144],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>LLM Infrastructure Cost: Enterprise AI breakdown &amp; Strategic Comparison<\/title>\n<meta name=\"description\" content=\"NewFangled Vision explains the LLM Infrastructure Cost, covering compute, data, orchestration, and governance costs for enterprises.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"LLM Infrastructure Cost: Enterprise AI breakdown &amp; Strategic Comparison\" \/>\n<meta property=\"og:description\" content=\"NewFangled Vision explains the LLM Infrastructure Cost, covering compute, data, orchestration, and governance costs for enterprises.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/\" \/>\n<meta property=\"og:site_name\" content=\"NewFangled VADY\" \/>\n<meta property=\"article:published_time\" content=\"2026-03-20T06:23:55+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/newfangled.io\/blog\/wp-content\/uploads\/2026\/03\/VADY-blog-16.jpg\" \/>\n<meta name=\"author\" content=\"Sahana Hanji\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Sahana Hanji\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"LLM Infrastructure Cost: Enterprise AI breakdown & Strategic Comparison","description":"NewFangled Vision explains the LLM Infrastructure Cost, covering compute, data, orchestration, and governance costs for enterprises.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/","og_locale":"en_US","og_type":"article","og_title":"LLM Infrastructure Cost: Enterprise AI breakdown & Strategic Comparison","og_description":"NewFangled Vision explains the LLM Infrastructure Cost, covering compute, data, orchestration, and governance costs for enterprises.","og_url":"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/","og_site_name":"NewFangled VADY","article_published_time":"2026-03-20T06:23:55+00:00","og_image":[{"url":"https:\/\/newfangled.io\/blog\/wp-content\/uploads\/2026\/03\/VADY-blog-16.jpg"}],"author":"Sahana Hanji","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Sahana Hanji","Est. reading time":"8 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/#article","isPartOf":{"@id":"https:\/\/newfangled.io\/blog\/llm-infrastructure-cost-enterprise-breakdown-strategic-comparison\/"},"author":{"name":"Sahana Hanji","@id":"https:\/\/newfangled.io\/blog\/#\/schema\/person\/fd787fdd51479b3d12971b83f0adce73"},"headline":"LLM Infrastructure Cost: Enterprise Breakdown &#038; 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Strategic Comparison"}]},{"@type":"WebSite","@id":"https:\/\/newfangled.io\/blog\/#website","url":"https:\/\/newfangled.io\/blog\/","name":"NewFangled VADY","description":"NewFangled VADY","publisher":{"@id":"https:\/\/newfangled.io\/blog\/#organization"},"alternateName":"VADY","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/newfangled.io\/blog\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/newfangled.io\/blog\/#organization","name":"NewFangled VADY","url":"https:\/\/newfangled.io\/blog\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/newfangled.io\/blog\/#\/schema\/logo\/image\/","url":"https:\/\/newfangled.io\/blog\/wp-content\/uploads\/2023\/04\/logo.png","contentUrl":"https:\/\/newfangled.io\/blog\/wp-content\/uploads\/2023\/04\/logo.png","width":561,"height":165,"caption":"NewFangled VADY"},"image":{"@id":"https:\/\/newfangled.io\/blog\/#\/schema\/logo\/image\/"}},{"@type":"Person","@id":"https:\/\/newfangled.io\/blog\/#\/schema\/person\/fd787fdd51479b3d12971b83f0adce73","name":"Sahana Hanji","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/newfangled.io\/blog\/#\/schema\/person\/image\/","url":"https:\/\/newfangled.io\/blog\/wp-content\/uploads\/2025\/05\/SahanaH-2.png","contentUrl":"https:\/\/newfangled.io\/blog\/wp-content\/uploads\/2025\/05\/SahanaH-2.png","caption":"Sahana Hanji"},"description":"I work at NewFangled Vision, a 6-year-old private GenAI startup from India. We build enterprise-grade AI systems without large LLMs or heavy GPU dependence, with a mission to make AI a seamless, must-have capability for every organization\u2014without complexity or hassle. 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