{"id":5451,"date":"2026-08-03T17:43:24","date_gmt":"2026-08-03T08:43:24","guid":{"rendered":"https:\/\/smilesoftware.org\/?p=5451"},"modified":"2026-08-03T17:43:26","modified_gmt":"2026-08-03T08:43:26","slug":"ai%e3%81%a7%e4%bc%9a%e8%ad%b0%e5%be%8c%e6%a5%ad%e5%8b%99%e3%82%92%e5%8a%b9%e7%8e%87%e5%8c%96%e3%80%82%e8%ad%b0%e4%ba%8b%e9%8c%b2%e8%a6%81%e7%b4%84%e3%81%a8%e3%82%a2%e3%82%af%e3%82%b7%e3%83%a7%e3%83%b3","status":"publish","type":"post","link":"https:\/\/smilesoftware.org\/en\/ai%E3%81%A7%E4%BC%9A%E8%AD%B0%E5%BE%8C%E6%A5%AD%E5%8B%99%E3%82%92%E5%8A%B9%E7%8E%87%E5%8C%96%E8%AD%B0%E4%BA%8B%E9%8C%B2%E8%A6%81%E7%B4%84%E3%81%A8%E3%82%A2%E3%82%AF%E3%82%B7%E3%83%A7%E3%83%B3\/","title":{"rendered":"Internal PoC: Using AI to Streamline Post-Meeting Work with Meeting Summarization and Action Item Extraction"},"content":{"rendered":"<div class=\"wp-block-group smile-post-content\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><header class=\"smile-article-header\"><div><span class=\"smile-category-pill\">Project<\/span><span class=\"smile-date\"><\/span><\/div><h1 class=\"smile-article-title\">Internal PoC: Using AI to Streamline Post-Meeting Work with Meeting Summarization and Action Item Extraction<\/h1><p class=\"smile-excerpt\">Within internal project and sales teams, organizing meeting outcomes, identifying action items, and sharing them with stakeholders after each meeting required a considerable amount of manual effort. To address this challenge, SMILE conducted an AI Assistant PoC that combines speech recognition and large language models (LLMs). The solution automatically summarizes meeting content, extracts action items with assigned owners and due dates, and generates draft emails for sharing meeting outcomes with relevant stakeholders.<\/p><\/header>\n\n\n<ul style=\"color:#475569;font-size:17px\" class=\"wp-block-list has-text-color has-link-color wp-elements-a97bbeef2b338f0f341f050f351ef585\">\n<li><strong>Industry \/ Target:<\/strong> Internal Projects \/ Sales Operations<\/li>\n\n\n\n<li><strong>Challenge:<\/strong> Creating post-meeting summaries, organizing action items, and sharing outcomes required significant manual effort and often led to missed information or overlooked tasks<\/li>\n\n\n\n<li><strong>Implementation Details:<\/strong> Meeting summarization, action item extraction, and email draft generation using Speech-to-Text and LLMs<\/li>\n\n\n\n<li><strong>SMILE\u2019s Scope of Support:<\/strong> Prompt and rule design, speech recognition integration, meeting summarization, action item extraction, email and task integration, and review workflow implementation<\/li>\n\n\n\n<li><strong>Development Period:<\/strong> 3 months<\/li>\n\n\n\n<li><strong>Team Size:<\/strong> 2 members \/ 6MM<\/li>\n\n\n\n<li><strong>Deployment Scale:<\/strong> One AI Assistant Platform Integrated with Calendar, Email, and Task Services<\/li>\n\n\n\n<li><strong>Implementation Benefits:<\/strong> The system automatically generates draft meeting minutes and action items immediately after each meeting, streamlining the review and sharing process.<\/li>\n<\/ul>\n\n\n<nav class=\"smile-toc\" aria-label=\"Table of Contents\"><h2 class=\"smile-toc__title\">Table of Contents<\/h2><div class=\"smile-toc__grid\"><a class=\"smile-toc__item\" href=\"#section-1\"><b class=\"smile-toc__number\">01<\/b><span class=\"smile-toc__label\">Customer Challenges<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-2\"><b class=\"smile-toc__number\">02<\/b><span class=\"smile-toc__label\">Project Objectives<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-3\"><b class=\"smile-toc__number\">03<\/b><span class=\"smile-toc__label\">SMILE\u2019s Scope of Support<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-4\"><b class=\"smile-toc__number\">04<\/b><span class=\"smile-toc__label\">Key Development and Improvement Points<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-5\"><b class=\"smile-toc__number\">05<\/b><span class=\"smile-toc__label\">Technologies Used<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-6\"><b class=\"smile-toc__number\">06<\/b><span class=\"smile-toc__label\">Technical Challenges and How We Addressed Them<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-7\"><b class=\"smile-toc__number\">07<\/b><span class=\"smile-toc__label\">Implementation Benefits<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-8\"><b class=\"smile-toc__number\">08<\/b><span class=\"smile-toc__label\">Key points for an offshore development structure<\/span><\/a><a class=\"smile-toc__item\" href=\"#section-9\"><b class=\"smile-toc__number\">09<\/b><span class=\"smile-toc__label\">Conclusion<\/span><\/a><\/div><\/nav>\n\n\n<div id=\"section-1\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">01<\/div><h2 class=\"smile-section__title\">Customer Challenges<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">In internal meetings, the workload extends beyond the discussion itself to the post-meeting organization of information. Participants need to review the meeting content, summarize the key points, identify task owners, and, when necessary, send follow-up emails or create tasks for relevant stakeholders.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">This series of tasks is time-consuming, and as meetings become larger or cover more topics, the risk of missed follow-ups and inconsistent understanding increases. In particular, if task owners and due dates are not clearly documented, subsequent progress tracking can be affected. A solution was therefore needed to reduce post-meeting administrative work while improving the clarity and traceability of action items.<\/p>\n<\/div><\/div>\n\n\n\n<div id=\"section-2\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">02<\/div><h2 class=\"smile-section__title\">Project Objectives<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">The objective of this PoC was to reduce the effort required for post-meeting summarization and action item organization, making it easier to turn meeting discussions into clear and actionable next steps.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">The goal was not simply to shorten meeting transcripts, but to identify key discussion points, extract action items with assigned owners and due dates, and present the results in a format that is easy to share. In addition, the PoC aimed to evaluate the practical level of AI assistance in real business workflows, assuming that AI-generated outputs would be reviewed by human users before being used.<\/p>\n<\/div><\/div>\n\n\n\n<div id=\"section-3\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">03<\/div><h2 class=\"smile-section__title\">SMILE\u2019s Scope of Support<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">SMILE was responsible for the design and implementation of an AI Assistant PoC to support post-meeting workflows. The primary scope of work included the following:<\/p>\n\n\n<ul class=\"smile-list\"><li>Prompt engineering and rule design for meeting content analysis and summarization<\/li><li>Implementation of a speech-to-text pipeline through Speech-to-Text integration<\/li><li>Implementation of an LLM-based meeting summarization feature<\/li><li>Design of the extraction logic for action items, assignees, and due dates<\/li><li>Output design for email draft generation and task system integration<\/li><li>Implementation of a review workflow that enables users to easily perform final verification<\/li><\/ul>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">A key principle of this PoC was that AI-generated outputs were not intended to be treated as final information. Instead, the solution was designed as an assistive tool, with the assumption that meeting participants would review and validate the results before use.<\/p>\n<\/div><\/div>\n\n\n\n<div id=\"section-4\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">04<\/div><h2 class=\"smile-section__title\">Key Development and Improvement Points<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">This PoC focused not only on automatically summarizing meeting content but also on presenting the results in a format that is immediately useful for day-to-day operations. After a meeting, what organizations truly need is not a lengthy summary, but a clear understanding of what was decided, who is responsible for each action item, and when it should be completed.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">To achieve this, the output was designed around a workflow consisting of key point summarization, action item extraction, assignee and due date identification, and draft generation for sharing. As a result, users no longer need to create meeting minutes from scratch; instead, they can simply review and refine the AI-generated draft, significantly reducing post-meeting administrative effort.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">In addition, meeting discussions often contain ambiguous expressions and context-dependent statements, making it important to prevent the AI from making overly autonomous judgments. Therefore, the solution was designed on the assumption that project managers or meeting participants would make the final decisions. By combining AI-generated outputs with a user-friendly review interface and output format, the PoC aimed to strike a practical balance between automation and human validation.<\/p>\n<\/div><\/div>\n\n\n\n<div id=\"section-5\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">05<\/div><h2 class=\"smile-section__title\">Technologies Used<\/h2><\/div>\n\n<div class=\"smile-evidence-panels\"><article class=\"smile-evidence-panel\"><div class=\"smile-evidence-panel__mark\"><span class=\"smile-evidence-panel__icon\" aria-hidden=\"true\"><svg class=\"smile-ui-icon smile-ui-icon--market\" viewbox=\"0 0 64 64\" aria-hidden=\"true\" focusable=\"false\" stroke=\"currentColor\"><path d=\"M10 50h44\"\/><path d=\"M16 42 28 30l8 8 16-20\"\/><path d=\"M40 18h12v12\"\/><\/svg><\/span><\/div><div class=\"smile-evidence-panel__body\"><h3 class=\"smile-evidence-panel__title\">Frontend<\/h3><p>The solution leveraged the review interface within Google Workspace, enabling users to easily review, edit, and validate AI-generated summaries and action items before they were finalized.<\/p><\/div><\/article><article class=\"smile-evidence-panel\"><div class=\"smile-evidence-panel__mark\"><span class=\"smile-evidence-panel__icon\" aria-hidden=\"true\"><svg class=\"smile-ui-icon smile-ui-icon--energy\" viewbox=\"0 0 64 64\" aria-hidden=\"true\" focusable=\"false\" stroke=\"currentColor\"><path d=\"M30 6 14 36h15l-5 22 20-34H29z\"\/><\/svg><\/span><\/div><div class=\"smile-evidence-panel__body\"><h3 class=\"smile-evidence-panel__title\">Backend<\/h3><p>A Python-based workflow was implemented to provide an end-to-end pipeline covering speech processing, meeting summarization, action item extraction, and integration with connected services.<\/p><\/div><\/article><article class=\"smile-evidence-panel\"><div class=\"smile-evidence-panel__mark\"><span class=\"smile-evidence-panel__icon\" aria-hidden=\"true\"><svg class=\"smile-ui-icon smile-ui-icon--document\" viewbox=\"0 0 64 64\" aria-hidden=\"true\" focusable=\"false\" stroke=\"currentColor\"><path d=\"M18 8h20l10 10v38H18z\"\/><path d=\"M38 8v12h10\"\/><path d=\"M24 32h18\"\/><path d=\"M24 42h18\"\/><path d=\"M24 22h8\"\/><\/svg><\/span><\/div><div class=\"smile-evidence-panel__body\"><h3 class=\"smile-evidence-panel__title\">Data Management<\/h3><p>Google Drive and internal storage were used to manage meeting-related data and AI-generated outputs in a centralized manner.<\/p><\/div><\/article><article class=\"smile-evidence-panel\"><div class=\"smile-evidence-panel__mark\"><span class=\"smile-evidence-panel__icon\" aria-hidden=\"true\"><svg class=\"smile-ui-icon smile-ui-icon--refactor\" viewbox=\"0 0 64 64\" aria-hidden=\"true\" focusable=\"false\" stroke=\"currentColor\"><circle cx=\"21\" cy=\"20\" r=\"6\"\/><circle cx=\"43\" cy=\"44\" r=\"6\"\/><path d=\"M27 20h10c7 0 11 4 11 11v7\"\/><path d=\"m42 32 6 6 6-6\"\/><path d=\"M37 44H27c-7 0-11-4-11-11v-7\"\/><path d=\"m22 32-6-6-6 6\"\/><\/svg><\/span><\/div><div class=\"smile-evidence-panel__body\"><h3 class=\"smile-evidence-panel__title\">AI Utilization<\/h3><p>In addition to converting speech into text using Speech-to-Text, the solution leverages LLMs to generate meeting summaries and extract action items. The focus is not only on producing readable meeting minutes but also on organizing information in a way that supports clear follow-up actions.<\/p><\/div><\/article><article class=\"smile-evidence-panel\"><div class=\"smile-evidence-panel__mark\"><span class=\"smile-evidence-panel__icon\" aria-hidden=\"true\"><svg class=\"smile-ui-icon smile-ui-icon--cost\" viewbox=\"0 0 64 64\" aria-hidden=\"true\" focusable=\"false\" stroke=\"currentColor\"><circle cx=\"32\" cy=\"32\" r=\"20\"\/><path d=\"M32 18v28\"\/><path d=\"M40 24c-2-4-14-5-16 1-3 8 17 5 14 14-2 6-14 5-17 0\"\/><\/svg><\/span><\/div><div class=\"smile-evidence-panel__body\"><h3 class=\"smile-evidence-panel__title\">Cloud &amp; Integration<\/h3><p>The PoC was built on Google Cloud and Google Workspace, with an architecture designed for integration with Google Calendar, Gmail, and task management workflows.<\/p><\/div><\/article><article class=\"smile-evidence-panel\"><div class=\"smile-evidence-panel__mark\"><span class=\"smile-evidence-panel__icon\" aria-hidden=\"true\"><svg class=\"smile-ui-icon smile-ui-icon--operations\" viewbox=\"0 0 64 64\" aria-hidden=\"true\" focusable=\"false\" stroke=\"currentColor\"><circle cx=\"32\" cy=\"32\" r=\"9\"\/><path d=\"M32 8v8\"\/><path d=\"M32 48v8\"\/><path d=\"m15 15 6 6\"\/><path d=\"m43 43 6 6\"\/><path d=\"M8 32h8\"\/><path d=\"M48 32h8\"\/><path d=\"m15 49 6-6\"\/><path d=\"m43 21 6-6\"\/><\/svg><\/span><\/div><div class=\"smile-evidence-panel__body\"><h3 class=\"smile-evidence-panel__title\">Other<\/h3><p>Prompt engineering was combined with human review to achieve a balance between output accuracy and operational practicality.<\/p><\/div><\/article><\/div><\/div><\/div>\n\n\n\n<div id=\"section-6\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">06<\/div><h2 class=\"smile-section__title\">Technical Challenges and How We Addressed Them<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">One of the biggest challenges was consistently extracting action items that were meaningful in real business workflows from meeting discussions. Conversations often contain abbreviated expressions and ambiguous wording, and the order of speakers alone is not always sufficient to clearly identify task owners or due dates.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">To address this challenge, SMILE clearly separated the responsibilities of meeting summarization and action item extraction, while refining prompts and output rules to present task details, assignees, and due dates in a structured and easy-to-use format. The outputs were also designed at an appropriate level of granularity to support downstream processes, including email draft generation and integration with task management systems, making them readily usable in subsequent business workflows.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">Furthermore, to ensure that AI-generated outputs were not treated as final decisions, the solution was designed around a human-centered review workflow. The PoC enables participants to review, edit, and validate AI-generated results before they are used, ensuring both the accuracy of the outputs and their practical applicability in real-world operations.<\/p>\n<\/div><\/div>\n\n\n\n<div id=\"section-7\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">07<\/div><h2 class=\"smile-section__title\">Implementation Benefits<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">This PoC enabled the automatic generation of draft meeting summaries, action items, assignees, and due dates immediately after each meeting. As a result, the time required for post-meeting administrative work was significantly reduced, while also helping minimize missed follow-up tasks and improve the clarity of individual responsibilities during execution.<\/p>\n<\/div><\/div>\n\n\n\n<div id=\"section-8\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">08<\/div><h2 class=\"smile-section__title\">Key points for an offshore development structure<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">In this PoC, SMILE adopted a collaborative development model between the Japan and Vietnam teams. The Japan side defined the desired operational workflow and clarified the challenges in post-meeting tasks, while the Vietnam development team implemented the solution based on the agreed requirements. Acting as a bridge, the BrSE continuously aligned business intent, expected outputs, and evaluation criteria for AI-generated results, minimizing differences in interpretation and ensuring the overall quality of the PoC.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">In addition, specifications and review criteria were shared between the Japan and Vietnam teams. During testing, the team evaluated not only the quality of the meeting summaries but also the clarity of action items, the representation of assignees and due dates, and the ease of reviewing the generated outputs. By maintaining short feedback and validation cycles, the team established a process that allowed the PoC to be evaluated under conditions that closely resembled real-world business operations.<\/p>\n<\/div><\/div>\n\n\n\n<div id=\"section-9\" class=\"wp-block-group smile-section\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"smile-section__head\"><div class=\"smile-section__number\">09<\/div><h2 class=\"smile-section__title\">Conclusion<\/h2><\/div>\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">Creating meeting summaries and organizing follow-up tasks are often overlooked yet time-consuming parts of everyday business operations. In this PoC, SMILE validated an approach that leverages AI to reduce this workload while structuring the outputs in a way that is practical for real-world use, assuming that users perform the final review and validation before the results are applied.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:16px\">Designing workflows that transform meeting discussions into actionable next steps is a common challenge for many organizations. Rather than focusing solely on meeting minute generation, this PoC rethinks the entire post-meeting workflow, including action item management and information sharing. It serves as a practical reference for organizations looking to leverage AI to improve the efficiency of post-meeting operations.<\/p>\n<\/div><\/div>\n\n\n<section class=\"smile-article-cta\"><div class=\"smile-article-cta__label\">SMILE Support<\/div><h2>Start a Consultation on GX and DX Initiatives<\/h2><p>From assessing your current situation to implementing systems and improving operations, we work with you to design an approach that fits your company\u2019s needs.<\/p><ul class=\"smile-list\"><li>We can help clarify issues in your current operations and data.<\/li><li>You can design implementation steps that fit your organization\u2019s structure.<\/li><li>You can continue building a framework that remains easy to operate after implementation.<\/li><li>You can use data to verify results and make ongoing improvements.<\/li><li>You can start exploring AI and IoT applications in the areas where they are most needed.<\/li><\/ul><a class=\"smile-article-cta__button\" href=\"\/en\/contact\/\">Contact us<\/a><\/section><\/div><\/div>","protected":false},"excerpt":{"rendered":"<p>\u793e\u5185\u4f1a\u8b70\u3067\u306f\u3001\u8b70\u8ad6\u305d\u306e\u3082\u306e\u3060\u3051\u3067\u306a\u304f\u3001\u7d42\u4e86\u5f8c\u306e\u60c5\u5831\u6574\u7406\u306b\u3082\u8ca0&hellip;&nbsp;<a href=\"https:\/\/smilesoftware.org\/en\/ai%E3%81%A7%E4%BC%9A%E8%AD%B0%E5%BE%8C%E6%A5%AD%E5%8B%99%E3%82%92%E5%8A%B9%E7%8E%87%E5%8C%96%E8%AD%B0%E4%BA%8B%E9%8C%B2%E8%A6%81%E7%B4%84%E3%81%A8%E3%82%A2%E3%82%AF%E3%82%B7%E3%83%A7%E3%83%B3\/\" class=\"\" rel=\"bookmark\">Read More &raquo;<span class=\"screen-reader-text\">Internal PoC: Using AI to Streamline Post-Meeting Work with Meeting Summarization and Action Item Extraction<\/span><\/a><\/p>","protected":false},"author":2,"featured_media":5450,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"_themeisle_gutenberg_block_has_review":false,"_ti_tpc_template_sync":false,"_ti_tpc_template_id":"","footnotes":""},"categories":[17],"tags":[42,40,33,49],"class_list":["post-5451","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-project","tag-ai","tag-automation","tag-dx","tag-project-management"],"acf":[],"rttpg_featured_image_url":{"full":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image.png",1672,941,false],"landscape":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image.png",1672,941,false],"portraits":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image.png",1672,941,false],"thumbnail":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image-150x150.png",150,150,true],"medium":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image-300x169.png",300,169,true],"large":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image-1024x576.png",1024,576,true],"1536x1536":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image-1536x864.png",1536,864,true],"2048x2048":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image.png",1672,941,false],"trp-custom-language-flag":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image-18x10.png",18,10,true],"neve-blog":["https:\/\/smilesoftware.org\/wp-content\/uploads\/2026\/07\/redmine-1610-13409-featured-image-930x620.png",930,620,true]},"rttpg_author":{"display_name":"\u7b20\u539f \u840c","author_link":"https:\/\/smilesoftware.org\/en\/author\/chinh-man\/"},"rttpg_comment":0,"rttpg_category":"<a href=\"https:\/\/smilesoftware.org\/en\/category\/project\/\" rel=\"category tag\">Project<\/a>","rttpg_excerpt":"\u793e\u5185\u4f1a\u8b70\u3067\u306f\u3001\u8b70\u8ad6\u305d\u306e\u3082\u306e\u3060\u3051\u3067\u306a\u304f\u3001\u7d42\u4e86\u5f8c\u306e\u60c5\u5831\u6574\u7406\u306b\u3082\u8ca0&hellip;&nbsp;Read More 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