{"id":942,"date":"2025-05-06T09:15:41","date_gmt":"2025-05-06T09:15:41","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/all-things-azure\/?p=942"},"modified":"2025-05-07T00:40:38","modified_gmt":"2025-05-07T00:40:38","slug":"reinventing-legacy-app-modernization-crowdbotics-ai-native-platform-on-azure","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/all-things-azure\/reinventing-legacy-app-modernization-crowdbotics-ai-native-platform-on-azure\/","title":{"rendered":"Reinventing Legacy App Modernization: Crowdbotics&#8217; AI-Native Platform on Azure"},"content":{"rendered":"<p><span style=\"font-family: verdana, geneva, sans-serif;\">Author: <a href=\"https:\/\/www.linkedin.com\/in\/charath\/\">Charath Ranganathan<\/a>, CTO, Crowdbotics<\/span><\/p>\n<p>Modernizing legacy applications is one of the most daunting tasks facing enterprises today. These systems, often built decades ago using technologies like COBOL on mainframes, power critical business functions but are notoriously difficult, time-consuming, and expensive to update or replace. The process typically involves painstaking manual efforts to understand undocumented code, decipher complex interdependencies, and generate mountains of documentation before new requirements can even be drafted. Documenting these systems during a modernization project is further complicated by the need to generate documents for different user personae, e.g. business analysts, project managers, or developers.<\/p>\n<p>What if there was a better way? What if you could leverage AI to deeply understand your legacy applications, not just assess their structure, but comprehend their\u00a0<em>functionality<\/em>\u00a0and automatically generate the specifications needed for modernization?<\/p>\n<p>Introducing Crowdbotics\u2019 code-to-spec solution, an AI-native platform designed to revolutionize application development and modernization, built from the ground up on Microsoft Azure.<\/p>\n<h2 style=\"text-align: center;\"><iframe src=\"\/\/www.youtube.com\/embed\/6tzZHQ7pWUY\" width=\"560\" height=\"314\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/h2>\n<h2>The Challenge: Drowning in Legacy Complexity<\/h2>\n<p>Traditional modernization approaches often begin with static analysis or assessment tools. While these can map dependencies and identify code structures, they fall short of truly understanding\u00a0<em>what the application does<\/em>. Business analysts and product managers spend countless hours manually reverse-engineering logic, interviewing subject matter experts (if they still exist), and translating findings into the requirements for a new system. This process is slow, error-prone, and often results in incomplete or inaccurate specifications. To complicate things further, legacy systems are rarely monolithic; they are often intricate webs of interconnected, loosely-coupled components, which makes comprehensive understanding even harder.<\/p>\n<h2>Crowdbotics: From Code to Specification with AI<\/h2>\n<p>Crowdbotics takes a fundamentally different, AI-native approach. Instead of just scanning code, our platform ingests legacy codebases \u2013 along with any available documentation like READMEs and context like existing system documentation \u2013 and uses sophisticated AI models to decompose and\u00a0<em>understand<\/em>\u00a0the application&#8217;s purpose and function.<\/p>\n<p><a href=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/crowdbotics-arch-1.png\"><img decoding=\"async\" class=\"aligncenter wp-image-952 size-large\" src=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/crowdbotics-arch-1-1024x397.png\" alt=\"crowdbotics arch image\" width=\"1024\" height=\"397\" srcset=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/crowdbotics-arch-1-1024x397.png 1024w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/crowdbotics-arch-1-300x116.png 300w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/crowdbotics-arch-1-768x298.png 768w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/crowdbotics-arch-1-1536x596.png 1536w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/crowdbotics-arch-1.png 1934w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/p>\n<p>Imagine feeding the Crowdbotics platform a GitHub repository containing a classic mainframe application built with\u00a0COBOL, JCL, and CICS. Our AI gets to work:<\/p>\n<ol>\n<li><strong>Deep Analysis:<\/strong>\u00a0It goes beyond structural assessment. It analyzes the code, comments, and related artifacts to infer the application&#8217;s business logic, workflows, and data interactions.<\/li>\n<li><strong>Functional Decomposition:<\/strong>\u00a0The platform identifies, and groups related functions into logical units. It doesn&#8217;t just say &#8220;there&#8217;s a database&#8221;; it identifies functional blocks like &#8220;Transaction Processing,&#8221; &#8220;Reporting,&#8221; or &#8220;User Authentication.&#8221;<\/li>\n<li><strong>Requirements Generation:<\/strong>\u00a0Based on this deep understanding, Crowdbotics automatically generates detailed requirements documentation, akin to a Product Requirements Document (PRD). This includes:\n<ul>\n<li><strong>Inferred Functionality:<\/strong>\u00a0Clear descriptions of what specific parts of the application\u00a0<em>do<\/em>.<\/li>\n<li><strong>Logical Groupings: <\/strong>How functions cluster together.<\/li>\n<li><strong>User Types:<\/strong>\u00a0Identifies the types of users interacting with different parts of the system.<\/li>\n<li><strong>Acceptance Criteria:<\/strong>\u00a0Defines conditions for successful operation based on the inferred logic.<\/li>\n<li><strong>System Relationships:<\/strong>\u00a0Highlights dependencies and interactions between components, potentially visualized using concepts like the C4 model.<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p style=\"text-align: center;\">\n<p><a href=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/ContainerDiagramRounded.webp\"><img decoding=\"async\" class=\"wp-image-946 aligncenter\" src=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/ContainerDiagramRounded-1024x862.webp\" alt=\"\" width=\"602\" height=\"507\" srcset=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/ContainerDiagramRounded-1024x862.webp 1024w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/ContainerDiagramRounded-300x253.webp 300w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/ContainerDiagramRounded-768x647.webp 768w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/ContainerDiagramRounded.webp 1216w\" sizes=\"(max-width: 602px) 100vw, 602px\" \/><\/a><\/p>\n<p>This AI-generated understanding serves as a powerful foundation. You can use these insights and requirements to:<\/p>\n<ul>\n<li><strong>Generate New Software:<\/strong>\u00a0Automatically scaffold a modern application based on the derived specifications.<\/li>\n<li><strong>Maintain &amp; Enhance:<\/strong>\u00a0Understand the impact of changes, fix bugs more efficiently, or add new features to the legacy system with greater confidence.<\/li>\n<\/ul>\n<p>For business analysts, product managers, and development teams, this means drastically reduced manual effort, faster time-to-modernization, and lower risk of misinterpreting critical legacy functions.<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/CodeInsightsRounded.webp\"><img decoding=\"async\" class=\"aligncenter wp-image-943 size-medium\" src=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/CodeInsightsRounded-300x252.webp\" alt=\"\" width=\"300\" height=\"252\" srcset=\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/CodeInsightsRounded-300x252.webp 300w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/CodeInsightsRounded-1024x862.webp 1024w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/CodeInsightsRounded-768x646.webp 768w, https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2025\/05\/CodeInsightsRounded.webp 1218w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/a><\/p>\n<h3>Natively Built and Powered by Azure<\/h3>\n<p>Crowdbotics&#8217; power comes from its AI-native architecture, which is built and runs entirely on Microsoft Azure, leveraging the platform&#8217;s robust compute, AI, and application services:<\/p>\n<ul>\n<li><strong>Azure OpenAI Service:<\/strong>\u00a0At the heart of our understanding engine, we leverage Azure OpenAI&#8217;s large language models for sophisticated code analysis, inference, and requirements generation.<\/li>\n<li><strong>Azure Kubernetes Service (AKS) &amp; Azure App Service:<\/strong>\u00a0Our complex, agentic AI ensemble requires significant compute power. We run these demanding workloads across AKS and App Service, benefiting from Azure&#8217;s scalability and container orchestration capabilities. Our core code-to-spec engine \u00a0primarily runs on AKS.<\/li>\n<li><strong>Azure Functions:<\/strong>\u00a0The analysis pipeline itself is architected as microservices, with key components running efficiently and at-scale on Azure Functions.<\/li>\n<li><strong>Future-proofing with Fine-Tuning:<\/strong>\u00a0We are actively exploring fine-tuning AI models on Azure, specifically for challenging legacy codebases or domain-specific languages that may not be well-represented in pre-trained foundation models. This ensures continuous improvement in accuracy and capability.<\/li>\n<\/ul>\n<p>Building on Azure provides the scalability, security, and cutting-edge AI services necessary to handle the complexity of understanding and modernizing diverse legacy systems.<\/p>\n<h3>See It In Action and Get Started<\/h3>\n<p>Understanding legacy code is no longer just about static analysis; it&#8217;s about deep, functional comprehension powered by AI. Crowdbotics, running natively on Azure, provides the bridge from complex legacy systems to modern, well-specified applications.<\/p>\n<ul>\n<li><strong><a href=\"https:\/\/www.youtube.com\/watch?feature=shared&amp;v=6tzZHQ7pWUY\">Watch the Demo<\/a>:<\/strong> See how we analyze a COBOL application and generate requirements in our complementary YouTube video<\/li>\n<li><a href=\"https:\/\/azuremarketplace.microsoft.com\/en-us\/marketplace\/apps\/crowdboticscorporation1682618353390.cb_platform?tab=overview\"><strong>Try Crowdbotics:<\/strong>\u00a0<\/a>Get started with Crowdbotics directly from the Azure Marketplace.<\/li>\n<\/ul>\n<p>Stop drowning in inefficient, manual modernization processes and start modernizing with AI-driven clarity. Let Crowdbotics and Azure accelerate your journey to modern applications. Require intelligence.<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Author: Charath Ranganathan, CTO, Crowdbotics Modernizing legacy applications is one of the most daunting tasks facing enterprises today. These systems, often built decades ago using technologies like COBOL on mainframes, power critical business functions but are notoriously difficult, time-consuming, and expensive to update or replace. The process typically involves painstaking manual efforts to understand undocumented [&hellip;]<\/p>\n","protected":false},"author":172657,"featured_media":947,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[35,36,38,20],"tags":[],"class_list":["post-942","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-agents","category-ai-apps","category-app-development","category-developer-productivity"],"acf":[],"blog_post_summary":"<p>Author: Charath Ranganathan, CTO, Crowdbotics Modernizing legacy applications is one of the most daunting tasks facing enterprises today. These systems, often built decades ago using technologies like COBOL on mainframes, power critical business functions but are notoriously difficult, time-consuming, and expensive to update or replace. The process typically involves painstaking manual efforts to understand undocumented [&hellip;]<\/p>\n","_links":{"self":[{"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/posts\/942","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/users\/172657"}],"replies":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/comments?post=942"}],"version-history":[{"count":0,"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/posts\/942\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/media\/947"}],"wp:attachment":[{"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/media?parent=942"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/categories?post=942"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-json\/wp\/v2\/tags?post=942"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}