{"id":41927,"date":"2025-05-13T09:00:49","date_gmt":"2025-05-13T02:00:49","guid":{"rendered":"https:\/\/lacviet.vn\/?p=41927"},"modified":"2025-05-13T10:22:14","modified_gmt":"2025-05-13T03:22:14","slug":"retrieval-augmented-generation","status":"publish","type":"post","link":"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/","title":{"rendered":"RAG (Retrieval Augmented Generation) is what? Pattern RAG works?"},"content":{"rendered":"<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">In the era of information explosion, businesses are faced with a data volume is growing, stretching from internal to customer data, market. So how to medium business advantage is the huge amount of data just optimized the operation process? <\/span><b>Retrieval Augmented Generation (RAG)<\/b><span style=\"font-weight: 400;\"> privacy is the groundbreaking solution to help solve the problem.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">In the article below, let&#039;s <a href=\"https:\/\/lacviet.vn\/en\/\">Lac Viet<\/a> learn RAG is what? How does it work? The app highlights that businesses can apply.<\/span><\/p>\n<h2 style=\"text-align: left;\">1. RAG what is?<\/h2>\n<blockquote>\n<p style=\"text-align: justify;\"><b><i>RAG or Retrieval Augmented Generation <\/i><\/b><i><span style=\"font-weight: 400;\">is a method of combining information retrieval and module, student, content to create the natural feedback, accuracy by leveraging huge data warehouse to provide the most relevant information according to the context user.<\/span><\/i><\/p>\n<\/blockquote>\n<figure id=\"attachment_41930\" aria-describedby=\"caption-attachment-41930\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-41930 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-2.jpg\" alt=\"Retrieval Augmented Generation\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-2.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-2-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-2-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-41930\" class=\"wp-caption-text\">RAG combination of information retrieval and module, student, content to create the natural feedback<\/figcaption><\/figure>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">In the context of the business need quick response to the customer request, RAG become effective tools to help optimize interaction between businesses and customers via chatbot system faq or the application support service.<\/span><\/p>\n<p style=\"text-align: justify;\"><em>Two main components of RAG<\/em><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\">Retrieval Module (module access): <span style=\"font-weight: 400;\">This department is responsible for searching collect data from the stock available information such as the internal database, documentation or other online sources. This module ensures that the feedback is created always based on accurate information suitable.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Generation Module (module a): <span style=\"font-weight: 400;\">After the data is retrieved, this module will handle creating feedback using natural language through the language models, big (Large Language Models \u2013 LLM). The goal of the module is to create the coherent answer individualised user friendly.<\/span><\/li>\n<\/ul>\n<h2 style=\"text-align: left;\">2. RAG overcome the limitations of the model WHO traditional<\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">The model Generative AI tradition (as <a href=\"https:\/\/chatgpt.com\/\" target=\"_blank\" rel=\"nofollow noopener\">ChatGPT<\/a>), based primarily on data that has been trained earlier encounter many limitations when applied in practice:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\">Error \u201cHallucination\u201d (hallucinations information)<span style=\"font-weight: 400;\">: WHO created the information is not true or not in the training data. <\/span>For example<span style=\"font-weight: 400;\">: When the chatbot was asked about a new product launch recently, it can provide false information or even fabricated information does not exist.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Misinformation or outdated<span style=\"font-weight: 400;\">: ONE based only on the training data from specific time can&#039;t be updated with new information if not coach again. <\/span>For example<span style=\"font-weight: 400;\">: A trainer in 2021 could not know about the event or change in policies, business takes place in the year 2024.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Can&#039;t check the source information<span style=\"font-weight: 400;\">: Do not cite the source data when the reply, users can hardly verify the correctness of the information. <\/span>For example<span style=\"font-weight: 400;\">: In the field requires transparency as finance or legal, not knowing information is based on sources which is a big risk.<\/span><\/li>\n<\/ul>\n<figure id=\"attachment_42800\" aria-describedby=\"caption-attachment-42800\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" class=\"wp-image-42800 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a1.jpg\" alt=\"Retrieval Augmented Generation\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a1.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a1-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a1-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-42800\" class=\"wp-caption-text\">ChatGPT <span style=\"font-weight: 400;\">self-generated information is not true or not in the training data<\/span><\/figcaption><\/figure>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Retrieval Augmented Generation overcome these limitations by combining the ability to access new information correct from data sources external or internal to ensure the answer is not only true but also can be derived.<\/span><\/p>\n<p style=\"text-align: justify;\">For example: <span style=\"font-weight: 400;\">Suppose a business provides services to support customers using chatbot AI. When customers ask:<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">\u201c<em>Warranty policy of the products X what is the latest?<\/em>\u201d<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">WHO traditional<span style=\"font-weight: 400;\"> may answer based on old information or give answers general, do not update.<\/span><\/li>\n<li style=\"text-align: justify;\">RAG<span style=\"font-weight: 400;\"> will retrieve the information from the official database of the company to provide detailed answers updated: <\/span><span style=\"font-weight: 400;\">\u201c<em>Product X have warranty policy latest is 12 months, applicable from the date 1\/1\/2024 include replace parts for free in case of technical errors.<\/em>\u201d<\/span><\/li>\n<\/ul>\n<h2 style=\"text-align: left;\">3. How the activities of RAG Retrieval Augmented Generation<\/h2>\n<blockquote>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Retrieval system Augmented Generation (RAG) operate based on strict process consists of 5 main steps:<\/span><\/p>\n<ul>\n<li style=\"text-align: justify;\"><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-1-thu-thap-du-lieu\"><span style=\"font-weight: 400;\">Step 1: collect data<\/span><\/a><\/li>\n<li style=\"text-align: justify;\"><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-2-phan-chia-du-lieu\"><span style=\"font-weight: 400;\">Step 2: divide data<\/span><\/a><\/li>\n<li style=\"text-align: justify;\"><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-3-nhung-tai-lieu\"><span style=\"font-weight: 400;\">Step 3: Embed document<\/span><\/a><\/li>\n<li style=\"text-align: justify;\"><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-4-xu-ly-truy-van-nguoi-dung\"><span style=\"font-weight: 400;\">Step 4: Handling user queries<\/span><\/a><\/li>\n<li style=\"text-align: justify;\"><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-5-tao-phan-hoi-voi-llm\"><span style=\"font-weight: 400;\">Step 5: Create feedback with LLM<\/span><\/a><\/li>\n<\/ul>\n<\/blockquote>\n<h3 style=\"text-align: left;\">Step 1: collect data<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">The first process most important in the Retrieval Augmented Generation is collecting data by data privacy is the foundation for the system to operate efficiently. The system retrieves data from various sources, including:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\">Source business insider: guidance documents, technical reports, databases, customer, email, or transaction history. This is the main data system important to help RAG correct answer queries related to internal operations.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">External source<span style=\"font-weight: 400;\">: Expert articles, industry research, forum or data publicly online. Data source this ensures the system can provide information that is time comprehensive.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Calculator updates, main campus<\/span>c<span style=\"font-weight: 400;\"> your data is a top priority to ensure the quality of feedback to help businesses always have reliable information to make decisions.<\/span><\/p>\n<figure id=\"attachment_41931\" aria-describedby=\"caption-attachment-41931\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" class=\"wp-image-41931 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-3.jpg\" alt=\"Retrieval Augmented Generation\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-3.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-3-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-3-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-41931\" class=\"wp-caption-text\">The system is ld\u1eef data from various sources<\/figcaption><\/figure>\n<h3 style=\"text-align: left;\">Step 2: divide data<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">After collection, data is classified, organized in small clusters to increase efficiency in the retrieval.<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\">Classification mechanism<span style=\"font-weight: 400;\">: Based on the factors such as <\/span>theme<span style=\"font-weight: 400;\">, <\/span>type of information<span style=\"font-weight: 400;\">\u00a0or <\/span>features of use<span style=\"font-weight: 400;\">. For example, a business service provider, IT can split the data into categories such as \u201cmaintenance system\u201d, \u201csecurity solution\u201d or \u201ctechnical support\u201d.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Results achieved<span style=\"font-weight: 400;\">: System building a data warehouse structure in which each data item is associated with the keyword or context corresponds help to significantly reduce the processing time when the query is sent to.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">The division ensures Retrieval system Augmented Generation access information quickly and at the same time limiting the risks to provide information not related.<\/span><\/p>\n<h3 style=\"text-align: left;\">Step 3: Embed document<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Embed documents is an important step to transform text data into a form that the computer can understand and handle. This is done through the algorithm, deep learning (Deep Learning) to help convert text into performing the arithmetic (vector embeddings).<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\">Process operation<span style=\"font-weight: 400;\">: The language model as <\/span>BERT<span style=\"font-weight: 400;\">, <\/span>RoBERTa<span style=\"font-weight: 400;\">\u00a0or <\/span>Sentence Transformers<span style=\"font-weight: 400;\"> used for semantic analysis of each text segment to ensure data is represented correctly optimized.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Effect<span style=\"font-weight: 400;\">: Data after embed can be match semantics to the query of the user, regardless of the wording of them. For example, whether users asking \u201chow to fix the system?\u201d or \u201cfix IT how?\u201d the system all understand this is the same intent and retrieve the relevant documents.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Thanks to this step, RAG capable of handling complex queries in a smoother way to bring valuable feedback high.<\/span><\/p>\n<figure id=\"attachment_41933\" aria-describedby=\"caption-attachment-41933\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-41933 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-5.jpg\" alt=\"Retrieval Augmented Generation\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-5.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-5-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-5-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-41933\" class=\"wp-caption-text\">Convert text into performing arithmetic so that the computer can understand<\/figcaption><\/figure>\n<h3 style=\"text-align: left;\">Step 4: Handling user queries<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">When a user submits a query, the system RAG perform two main tasks: <\/span>semantic analysis, match information.<\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\">Semantic analysis: the Query is converted into performing vector similar data&#039;ve embedded, whereby the system to understand the real intention of the user. For example, if the query is <i>\u201cHow to make server maintenance efficiency?\u201d<\/i>\u00a0RAG will recognize the keyword \u201cmaintenance\u201d and \u201cservers\u201d to search for the matching documents.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Match information<span style=\"font-weight: 400;\">: Based on performances vector, the system searches the data similarities in the repository and returns the most accurate results.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">With the ability to handle natural language (Natural Language Processing \u2013 NLP), RAG not only answer questions but also provide additional information appropriate to help users have more comprehensive view of the issue.<\/span><\/p>\n<h3 style=\"text-align: left;\">Step 5: Create feedback with LLM<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">After retrieval of information, the last step is to use the model language (LLM) to create feedback. Model<\/span> <span style=\"font-weight: 400;\">integrated information access with context query. Then create natural feedback, seamless, consistent with the needs of users.<\/span><\/p>\n<figure id=\"attachment_41934\" aria-describedby=\"caption-attachment-41934\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-41934 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-6.jpg\" alt=\"Retrieval Augmented Generation\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-6.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-6-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-6-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-41934\" class=\"wp-caption-text\">RAG create natural feedback, seamless, and consistent with the needs of users<\/figcaption><\/figure>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">For example, If the user asked, <\/span><i><span style=\"font-weight: 400;\">\u201cI need instructions on how to secure intranet system\u201d<\/span><\/i><span style=\"font-weight: 400;\">the response from the Retrieval Augmented Generation can, including procedures for basic security and hints deployment of security tools modern.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">LLM provides not only information but also adjust the wording to match the communication style of the user who created the feeling like you are interacting with a real expert.<\/span><\/p>\n<h2 style=\"text-align: left;\">4. RAG brings the benefits for business?<\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Retrieval Augmented Generation (RAG) not only is an advanced technology which is also strategic solutions for businesses that want to optimize workflow, enhance performance. Here are the benefits that RAG bring help businesses not only overcome the challenges but also prevailed in a competitive environment:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\">Increased efficiency in the processing of information<span style=\"font-weight: 400;\">: Processing huge amount of data efficiently, thereby improving work productivity. Instead of losing hours and hours to just, sort data, the system automatically retrieve the correct information in just a few seconds.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Personalize customer experience<span style=\"font-weight: 400;\">: RAG doesn&#039;t just stop at answering questions, but also analysis of behavior, interests, status of each customer to give feedback accordingly.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Analysis provides timely information<span style=\"font-weight: 400;\">: The system can access the reports, market analysis, information about the latest trend or historical data in just a snap, help the management team make decisions based on real data have clear base.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Increased processing speed problems<span style=\"font-weight: 400;\">: When in a crisis, businesses can rely on RAG to quickly identify the causes, and implementing solutions efficiently.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Optimized hr<span style=\"font-weight: 400;\">: Instead of having a large team to handle information or answer the request from the client, the business can use the RAG to perform these tasks quickly effective.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Minimize errors<span style=\"font-weight: 400;\">: System access, auto-response eliminates the human error caused from it to avoid the costs incurred are not necessary.<\/span><\/li>\n<\/ul>\n<h2 id=\"5-5-ung-dung-noi-bat-cua-retrieval-augmented-generation\" class=\"ftwp-heading\">5. 5 outstanding application of Retrieval Augmented Generation<\/h2>\n<p>Applying RAG not only bring the flexibility, accuracy in information processing, but also open up many innovative solutions for the business operations.<\/p>\n<blockquote><p>Here are 5 apps highlights of RAG to help optimize workflow, increase operational efficiency.<\/p>\n<ul>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#5-1-he-thong-hoi-dap-nang-cao\">System faq advanced<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#5-2-truy-xuat-thong-tin-nhanh-chong\">Access quick information<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#5-3-cai-thien-dam-thoai-voi-chatbot\">Improved conversation with Chatbot<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#5-4-tao-va-tom-tat-noi-dung-chinh-xac\">Create and summary of contents exactly<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#5-5-ho-tro-dich-vu-khach-hang\">Support customer service<\/a><\/li>\n<\/ul>\n<\/blockquote>\n<h3 style=\"text-align: left;\">5.1 System faq advanced<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">System faq based on the RAG, not merely answer questions but also give the accurate feedback consistent with the context. Thanks to the ability to integrate data access auto-response, these systems are becoming an indispensable tool in an enterprise environment.<\/span><\/p>\n<figure id=\"attachment_41935\" aria-describedby=\"caption-attachment-41935\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-41935 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-7.jpg\" alt=\"Retrieval Augmented Generation\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-7.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-7-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-7-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-41935\" class=\"wp-caption-text\">RAG provides the accurate feedback, consistent with the context<\/figcaption><\/figure>\n<p style=\"text-align: justify;\"><b>How to RAG operated in the faq<\/b><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">When users take out of the question, Retrieval Augmented Generation, retrieving information from the database relevant in combination with the context query. For example, if new employees need to learn the internal processes, the system will provide material, suitable explanation help reduce the search time information.<\/span><\/p>\n<h3 style=\"text-align: left;\">5.2 Access to information quickly<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">One of the strong points of RAG is capable of handling provide information from a huge amount of data in just a snap useful for large enterprises where the data is stored in the warehouse complex. <\/span><span style=\"font-weight: 400;\">Such in the health sector, the system can support, doctor, access medical records, treatment history in just a few seconds helps improve the efficiency of health care.<\/span><\/p>\n<h3 style=\"text-align: left;\">5.3 Improve the conversation with the Chatbot<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Other with chatbot typically, the chatbot integrated RAG ability to provide feedback, carries in-depth, rich in context, even beyond the ability of the chatbot traditional. <\/span><span style=\"font-weight: 400;\">RAG not only based on the scenario programming available but also use real data to answer the query. Such in the field of ecommerce chatbot can provide detailed information about the products accompanied by reviews from previous customers.<\/span><\/p>\n<figure id=\"attachment_41936\" aria-describedby=\"caption-attachment-41936\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-41936 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-8.jpg\" alt=\"Ph\u01b0\u01a1ng ph\u00e1p RAG\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-8.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-8-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-8-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-41936\" class=\"wp-caption-text\">RAG ability to provide feedback, carries in-depth, rich in context<\/figcaption><\/figure>\n<p>Lac Viet Chatbot AI Assistant is a tools app using artificial intelligence to support business optimization tasks in operations management. At the same time, Vietnam Chatbot AI Assistant also has the ability to integrate into the management software, the other to synthetic data, research, analysis, assessments, predict overview.<\/p>\n<p style=\"text-align: justify;\"><b>Virtual assistant answered 24\/7 information internal business<\/b><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Lac Viet Chatbot AI Assistant support 24\/7 to answer any policies\/mode Financial accounting with any information, Questions &amp; Answers thanks to the integrated platform ChatGPT, Gemini ...<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Answer all of the information from the Document with all contexts, instead of searching manually.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Automatic synthesis of information to the user after a search in the Source data.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Auto-summary information when questions and answers on a document file in the archives Of quick test test full, read fast read enough help compliance implementation process.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><b>Support operational accounting<\/b><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Chatbot AI to answer any queries in real time right in functional statistics report help Leadership decisions quickly, reducing the time to explain the report.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tracking and analysis of financial indicators, warning fluctuations instant help businesses manage risks proactively.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Automation scheduling, Email reminders when to term liabilities \u2013 payments, increased experience with Customers\/suppliers.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Financial forecast accurately with AI analysis, historical data, predict trends, help plan financial efficiency.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><b>Optimal process lookup \u2013 approved<\/b><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Integrated in the management system documents, the register number, to help answer any queries in real time right in the workspace.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The analysis of data, business optimization, management accounting, to digitize processes approved.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: center;\">\t\t<div data-elementor-type=\"page\" data-elementor-id=\"42855\" class=\"elementor elementor-42855\" data-elementor-post-type=\"elementor_library\">\n\t\t\t\t<div class=\"elementor-element elementor-element-27ebb3b e-flex e-con-boxed e-con e-parent\" data-id=\"27ebb3b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-afbe822 elementor-widget elementor-widget-text-editor\" data-id=\"afbe822\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<blockquote><p style=\"text-align: justify;\"><span style=\"color: #ec5e20; font-size: 12pt;\"><strong>Do you know businesses are spending a lot of money to pay for staff looking for information?<\/strong><\/span><\/p><ul style=\"text-align: justify;\"><li><em><span style=\"color: #ec5e20;\"><strong>Of 1.8 hours per day<\/strong><\/span><\/em> employees spend out to search and collect information, the equivalent of 9.3 hours per week<\/li><li>Business loss <em><span style=\"color: #ec5e20;\"><strong>500 hours per year<\/strong><\/span><\/em> for employees to perform searches for information for work<\/li><li><em><span style=\"color: #ec5e20;\"><strong>63% leadership<\/strong><\/span><\/em> said the sharing of knowledge and information internal trouble, reduce the productivity of the business<\/li><\/ul><p style=\"text-align: justify;\"><span style=\"font-size: 12pt;\"><strong><a href=\"https:\/\/lacviet.vn\/en\/lv-chatbot-ai-assistant\/?utm_source=blog-AI&amp;utm_medium=anchortext-sp\" target=\"_blank\" rel=\"nofollow noopener\">Lac Viet Chatbot AI assistant<\/a> \u2013 Freeing up personnel to focus on creative work<\/strong><\/span><\/p><ul style=\"text-align: justify;\"><li>Virtual assistant process \u2013 approved LV Chatbot AI for Workflow: Access quick information, content summary, revise errors on file the signed<\/li><li>Virtual assistant accountant LV Chatbot AI assistant for Finance: remove input crafts, bring the data to the correct input, automatically prompt-term LIABILITIES \u2013 PAYMENTS, cash flow forecasting, warning of financial risks<\/li><li>Virtual assistant customer care LV CareBot AI assistant: Integrated Chat on multi-platform, feedback and customer requests quickly, consulting, flexible, not being constrained by fixed script<\/li><li>Virtual assistant hr LV Chatbot AI for HXM: save 70% time for HR and leadership, extract the entire database of candidates any file format, faq auto welfare policies, rules, regulations 24\/7, statistical, personnel, resources, business in few seconds.<\/li><\/ul><p style=\"text-align: justify;\"><a href=\"https:\/\/lacviet.vn\/en\/lv-chatbot-ai-assistant\/?utm_source=blog-AI&amp;utm_medium=banner\" target=\"_blank\" rel=\"nofollow noopener\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-42619\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/07\/lv-chatbot-ai-assistant.png\" alt=\"L\u1ea1c Vi\u1ec7t chatbot AI Assistant\" width=\"900\" height=\"600\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/07\/lv-chatbot-ai-assistant.png 900w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/07\/lv-chatbot-ai-assistant-768x512.png 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/07\/lv-chatbot-ai-assistant-18x12.png 18w\" sizes=\"(max-width: 900px) 100vw, 900px\" \/><\/a><\/p><p style=\"text-align: center;\"><a href=\"https:\/\/lacviet.vn\/en\/lv-chatbot-ai-assistant\/?utm_source=blog-AI&amp;utm_medium=xem-tinh-nang\" target=\"_blank\" rel=\"nofollow noopener\"><strong><em>SEE MORE FEATURES HERE<\/em><\/strong><\/a><\/p><p><strong>CONTACT INFORMATION:<\/strong><\/p><ul><li aria-level=\"1\">Lac Viet Computing Corporation<\/li><li aria-level=\"1\">Hotline:\u00a0<a class=\"text-is-phone-number\" href=\"tel:0901 555 063\" data-z-element-type=\"phone-number\">0901 555 063<\/a><span class=\"text\">\u00a0|\u00a0<\/span><a href=\"tel:(+84.28) 3842 3333\">(+84.28) 3842 3333<\/a><\/li><li aria-level=\"1\">Email:\u00a0<a href=\"mailto:info@lacviet.com.vn\">info@lacviet.vn<\/a>\u00a0\u2013 Website:\u00a0<a href=\"https:\/\/lacviet.vn\/en\/\">https:\/\/lacviet.vn<\/a><\/li><li aria-level=\"1\">Headquarters: 23 Nguyen Thi Huynh, P. 8, Q. Phu Nhuan, Ho Chi Minh city<\/li><\/ul><\/blockquote>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<\/p>\n<h3 style=\"text-align: left;\">5.4 Create content summary accurate<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">In the information age, the data processing huge volume of the condensed information understandable is a challenge. RAG business support, generate reports, content summary, quick help save time cost. <\/span><span style=\"font-weight: 400;\">For example in the field of journalism, reporters can use Retrieval Augmented Generation to summarize long articles into the main content accessible to readers.<\/span><\/p>\n<h3 style=\"text-align: left;\">5.5 Support customer service<\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">The ability to personalize customer feedback is the strong point of the RAG to help businesses build trust, increase the satisfaction level of customers.<\/span><\/p>\n<figure id=\"attachment_41937\" aria-describedby=\"caption-attachment-41937\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-41937 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-9.jpg\" alt=\"Ph\u01b0\u01a1ng ph\u00e1p RAG\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-9.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-9-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-9-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-41937\" class=\"wp-caption-text\">RAG ability to personalize customer feedback<\/figcaption><\/figure>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">RAG helps chatbot not only understand but also feedback according to personal style, based on purchase history, behavior, access or emotional state of the customer. In addition, the system also supports expert sales consultants in the product description, the proposed solution is based on the individual needs of each customer.<\/span><\/p>\n<h2 style=\"text-align: left;\">6. Process deployment RAG for business<\/h2>\n<p>The application of Retrieval Augmented Generation (RAG) into business operations not only in technology but also as an overall strategy, which should be done in a basically scientific. To ensure the system RAG bring practical value businesses need to comply with a deployment process clearly effective.<\/p>\n<blockquote><p>Here are 5 basic steps to help businesses optimize the integrated RAG into the internal system.<\/p>\n<ul>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-1-xac-dinh-nhu-cau-va-muc-tieu-cua-doanh-nghiep\">Step 1: Identify needs, goals of the business<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-2-chuan-bi-co-so-du-lieu-va-mo-hinh-ai\">Step 2: Prepare data base and model WHO<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-3-tich-hop-rag-vao-he-thong-hien-hanh\">Step 3: integrate RAG into the current system<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-4-kiem-thu-va-danh-gia-hieu-qua\">Step 4: testing efficiency rating<\/a><\/li>\n<li><a href=\"https:\/\/lacviet.vn\/en\/retrieval-augmented-generation\/#buoc-5-toi-uu-va-mo-rong-quy-mo\">Step 5: optimal scaling<\/a><\/li>\n<\/ul>\n<\/blockquote>\n<h3 style=\"text-align: left;\">Step 1: Determine the needs and goals of the business<\/h3>\n<h4><span style=\"font-weight: 400;\">To deploy successful Retrieval Augmented Generation<\/span><span style=\"font-weight: 400;\">the first step is to clearly define the target demand<\/span><span style=\"font-weight: 400;\"> of the business. This helps to ensure that the solution RAG matching strategy, bringing optimal efficiency.<\/span><\/h4>\n<p><b>Analysis of specific needs<\/b><span style=\"font-weight: 400;\">:<\/span><\/p>\n<ul>\n<li><span style=\"font-weight: 400;\">Enterprises need to improve the customer experience through chatbot?<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Need support staff lookup internal information quickly?<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Need to increase the accuracy for the report automatically?<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Need to enhance the ability to query data in real time?<\/span><\/li>\n<\/ul>\n<p><b>Define clear goals<\/b><span style=\"font-weight: 400;\">:<\/span><\/p>\n<ul>\n<li><span style=\"font-weight: 400;\">Discount <\/span>30%<span style=\"font-weight: 400;\"> response rate deviations from chatbot customer support.<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Increase the search speed, internal documents up <\/span>50%<span style=\"font-weight: 400;\">.<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Ensure the AI system provides information from the data source is updated.<\/span><\/li>\n<\/ul>\n<h3 style=\"text-align: left;\">Step 2: Prepare data base and model WHO<\/h3>\n<p><span style=\"font-weight: 400;\">The deployment RAG require business fully prepared <\/span><b>input data<\/b><span style=\"font-weight: 400;\"> and <\/span><b>models WHO available<\/b><span style=\"font-weight: 400;\"> to integrate effective.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Determine the type of data<\/b><span style=\"font-weight: 400;\">: Text data from internal documents, technical manuals, FAQs, information products\/services, customer data,...<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Standardize \u2013 cleaning data<\/b><span style=\"font-weight: 400;\">: Remove outdated data or incorrect. Ensure data clearly structured to WHO can access easily.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Prepare model WHO is there<\/b><span style=\"font-weight: 400;\">: Specify the language models are used (for example, GPT-3, GPT-4, or the custom model). Evaluate the possibility of integration of models with features to retrieve data.<\/span><\/li>\n<\/ul>\n<figure id=\"attachment_42802\" aria-describedby=\"caption-attachment-42802\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-42802 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a2.jpg\" alt=\"Retrieval Augmented Generation\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a2.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a2-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a2-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-42802\" class=\"wp-caption-text\">Fully prepared input data have the clear structure, has been cleaned<\/figcaption><\/figure>\n<h3 style=\"text-align: left;\">Step 3: integrate RAG into the current system<\/h3>\n<p><span style=\"font-weight: 400;\">When prepared the database and model WHO, the next step is <\/span>integrated Retrieval Augmented Generation into the system of the business<span style=\"font-weight: 400;\">.<\/span><\/p>\n<ul>\n<li>Select integrated solution suitable<span style=\"font-weight: 400;\">: <\/span>On-premise (on-site)<span style=\"font-weight: 400;\">: Suitable for businesses that need high data security; <\/span>Cloud-based (cloud)<span style=\"font-weight: 400;\">: Suitable for business needs the ability to expand quickly.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Connect database with the pattern AI<span style=\"font-weight: 400;\">: Use the API or framework support (for example: LangChain, Haystack) to connect between the data and model WHO.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Set the access and content<span style=\"font-weight: 400;\">: Specify the check points to ensure information is accurate traceability before model born answers.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Integrated with the current system<span style=\"font-weight: 400;\">: Integrate with CRM systems to chatbot RAG providing customer information accurately. Connection with the management system documentation to employee search internal information easily.<\/span><\/li>\n<\/ul>\n<p>The purpose of this step<span style=\"font-weight: 400;\"> is the help system of the RAG is connected, works in sync with the existing tools of business.<\/span><\/p>\n<h3 style=\"text-align: left;\">Step 4: test and evaluate the effectiveness<\/h3>\n<p><span style=\"font-weight: 400;\">After integration, it should proceed <\/span>test thoroughly<span style=\"font-weight: 400;\"> to ensure RAG operate effectively to meet goals.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Functional testing<span style=\"font-weight: 400;\">: Ensure pattern access and accurate data, provide suitable answers.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Test performance<span style=\"font-weight: 400;\">: Rated speed feedback, the ability to handle as many simultaneous queries.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Test security<span style=\"font-weight: 400;\">: System test to ensure no leaking sensitive data.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Evaluation results based on KPIs<span style=\"font-weight: 400;\">: Measure response rate, accuracy, speed search, and the level of satisfaction of users.<\/span><\/li>\n<\/ul>\n<figure id=\"attachment_42815\" aria-describedby=\"caption-attachment-42815\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-42815 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a3.jpg\" alt=\"RAG\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a3.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a3-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a3-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-42815\" class=\"wp-caption-text\">System test to ensure no leaking sensitive data<\/figcaption><\/figure>\n<h3 style=\"text-align: left;\">Step 5: optimal scaling<\/h3>\n<p><span style=\"font-weight: 400;\">After testing, evaluating success, business conduct <\/span>optimized scaling, deployment, Retrieval Augmented Generation<span style=\"font-weight: 400;\">.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>System optimization<\/strong>: Improving models to enhance the accuracy, speed feedback. At the same time, adjust the database to update with new information constantly.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Coaching model more data peculiarities<\/strong>: Customize the model to better fit the language needs of the business.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Scaling applied<\/strong>: Integrated RAG into many different parts, such as parts, customer support, legal department (lookup general legal regulations), The technical department (search assistance, guidance on repair, maintenance),...<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Periodic review<\/strong>: Continuous monitoring, system improvements to meet business needs change.<\/span><\/li>\n<\/ul>\n<p>Thanks to this step<b>, <\/b><span style=\"font-weight: 400;\">system RAG stable operation, the effect is applied on the interface width in the business.<\/span><\/p>\n<h2 style=\"text-align: left;\">7. Challenges when applying RAG in business<\/h2>\n<p>Deployment Retrieval Augmented Generation brings many advantages for the business but also come with little to no challenge. The identification solve these obstacles is the key to optimize the efficiency of the system RAG.<\/p>\n<h3 style=\"text-align: left;\">7.1 Data access to heterogeneous<\/h3>\n<p><span style=\"font-weight: 400;\">In the vast majority of business data is often stored in many different formats such as PDF, Word, Excel, or even no data structure from the email and notes. Make the extracted information to train the model <\/span>Retrieval Augmented Generation (RAG)<span style=\"font-weight: 400;\"> much difficulty. Data heterogeneity can reduce the accuracy of information traceability leads to results not consistently affect the operational efficiency of the chatbot.<\/span><\/p>\n<figure id=\"attachment_42816\" aria-describedby=\"caption-attachment-42816\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-42816 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a4.jpg\" alt=\"RAG\" width=\"800\" height=\"500\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a4.jpg 800w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a4-768x480.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/11\/retrieval-augmented-generation-a4-18x12.jpg 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-42816\" class=\"wp-caption-text\">Data stored in various formats such as PDF, Word, Excel, or even no data structure<\/figcaption><\/figure>\n<p><b>Solution fix<\/b><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">Business needs planning, standardized data before deploying RAG. This process includes:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Sort, classify data<span style=\"font-weight: 400;\"> according to each group of functions or departments.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Data conversion<span style=\"font-weight: 400;\"> to the unified format such as JSON or XML for easy handling.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Use OCR technology<span style=\"font-weight: 400;\"> combined with <\/span>AI-Data Extraction<span style=\"font-weight: 400;\"> in order to automatically extract information from the document does not structure.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Training constantly updated<span style=\"font-weight: 400;\"> to chatbot properly understand the context, improving the ability to retrieve information.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Solution <\/span>Server AI<span style=\"font-weight: 400;\"> of Lac Viet App has the ability to automatically identify, collect information from the text with no structure. Complete control over data, put into ONE, easy trainer WHO fits your specific needs does not depend on the service Tuesday.<\/span><\/p>\n<p style=\"text-align: center;\">\t\t<div data-elementor-type=\"page\" data-elementor-id=\"43135\" class=\"elementor elementor-43135\" data-elementor-post-type=\"elementor_library\">\n\t\t\t\t<div class=\"elementor-element elementor-element-552097f e-flex e-con-boxed e-con e-parent\" data-id=\"552097f\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-53b469b elementor-widget elementor-widget-text-editor\" data-id=\"53b469b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<blockquote><p style=\"text-align: justify;\"><em>According to the survey 2023 by IDC, <span style=\"color: #ff6600;\"><strong>more<\/strong><\/span> <span style=\"color: #ff6600;\"><strong>95%<\/strong><\/span> the business world has started to convert numbers with different steps from learn, study, to start the deployment and implementation. Is step premise of the transition of <span style=\"color: #ff6600;\"><strong>document digitization \u2013 the opportunity to move his business in Vietnam<\/strong><\/span> when the state put in place policies to support businesses during the digitized.<\/em><\/p><p style=\"text-align: justify;\"><strong>Lac Viet \u2013 the first successful deployment <a href=\"https:\/\/lacviet.vn\/en\/lv-local-ai-server-systems\/?utm_source=blog-so-hoa&amp;utm_medium=anchortext-sp\" target=\"_blank\" rel=\"nofollow noopener\">service digitization<\/a> OCR built-in AI for business<\/strong><\/p><ul><li style=\"text-align: justify;\"><span style=\"color: #ff6600;\"><b>OCR technology <\/b><\/span>character recognition advanced, has the ability to convert images and scan documents into digital text with high accuracy, supports multi-languages, including English accented.<\/li><li style=\"text-align: justify;\">Automatically recognizes, collects the information from the document does not have the structure (such as invoices, contracts, reports).<\/li><li style=\"text-align: justify;\">Automatic sorting, converting these documents into a format that data (such as JSON), ready for storage, retrieval or integration into other systems.<\/li><li style=\"text-align: justify;\">Integrated features <span style=\"color: #ff6600;\"><strong>translation auto<\/strong><\/span> for digitized documents, support <span style=\"color: #ff6600;\"><strong>more than 87 languages<\/strong><\/span>. Supported by LLM, features ensure the quality of translation retains context and meaning, especially useful for documents or international businesses with multi-national operations.<\/li><li style=\"text-align: justify;\"><span style=\"color: #ff6600;\"><strong>Integrated chatbot AI<\/strong> <\/span>smart allows queries to search data from the internal documents quickly.<\/li><\/ul><p style=\"text-align: justify;\"><a href=\"https:\/\/lacviet.vn\/en\/lv-local-ai-server-systems\/?utm_source=blog-so-hoa&amp;utm_medium=banner\" target=\"_blank\" rel=\"nofollow noopener\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-42776 size-full\" src=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/12\/dich-vu-so-hoa-lac-viet.jpg\" alt=\"d\u1ecbch v\u1ee5 s\u1ed1 h\u00f3a L\u1ea1c Vi\u1ec7t\" width=\"900\" height=\"600\" srcset=\"https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/12\/dich-vu-so-hoa-lac-viet.jpg 900w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/12\/dich-vu-so-hoa-lac-viet-768x512.jpg 768w, https:\/\/lacviet.vn\/wp-content\/uploads\/2024\/12\/dich-vu-so-hoa-lac-viet-18x12.jpg 18w\" sizes=\"(max-width: 900px) 100vw, 900px\" \/><\/a><\/p><p style=\"text-align: center;\"><a href=\"https:\/\/lacviet.vn\/en\/lv-local-ai-server-systems\/?utm_source=blog-so-hoa&amp;utm_medium=xem-tinh-nang\" target=\"_blank\" rel=\"nofollow noopener\"><strong><em>SEE THE DETAILED FEATURES OF THE NUMERICAL SOLUTION HERE.<\/em><\/strong><\/a><\/p><p style=\"text-align: justify;\"><strong>CONTACT INFORMATION:<\/strong><\/p><ul><li>Lac Viet Computing Corporation<\/li><li>Hotline:\u00a0<a class=\"text-is-phone-number\" href=\"tel:0901 555 063\" data-z-element-type=\"phone-number\">0901 555 063<\/a><span class=\"text\">\u00a0|\u00a0<\/span><a href=\"tel:(+84.28) 3842 3333\">(+84.28) 3842 3333<\/a><\/li><li>Email:\u00a0<a href=\"mailto:info@lacviet.com.vn\">info@lacviet.vn<\/a>\u00a0\u2013 Website:\u00a0<a href=\"https:\/\/lacviet.vn\/en\/\">https:\/\/lacviet.vn<\/a><\/li><li>Headquarters: 23 Nguyen Thi Huynh, P. 8, Q. Phu Nhuan, Ho Chi Minh city<\/li><\/ul><\/blockquote>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<\/p>\n<h3 style=\"text-align: left;\">7.2 Cost of initial deployment<\/h3>\n<p><span style=\"font-weight: 400;\">Applying RAG on chatbot WHO require the cost of the initial investment is quite big for infrastructure, technology, personnel expertise, systems integration. This can be big hurdle for the small and medium enterprises, which have limited budget for the project number conversion.<\/span><\/p>\n<p><b>Solution fix<\/b><span style=\"font-weight: 400;\">:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Select implementation partner prestigious<span style=\"font-weight: 400;\"> as <\/span>Lac Viet<span style=\"font-weight: 400;\">supply unit <\/span>LV Chatbot AI Assistant<span style=\"font-weight: 400;\"> with many services flexibility, including the form of rent, or buy software.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Integrated gradually phased<span style=\"font-weight: 400;\"> to allocate the budget reasonable, reduce the financial pressure.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Leverage the infrastructure available<span style=\"font-weight: 400;\">integrated with systems such as CRM, ERP to optimize investment costs.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Support consultant demo<span style=\"font-weight: 400;\"> free from our expert team to ensure the solution matching the real needs of the business.<\/span><\/li>\n<\/ul>\n<p><b>Retrieval Augmented Generation <\/b><span style=\"font-weight: 400;\">not only is an advanced technology that is also a powerful tool to help businesses optimize the ability to access information, improve customer experience, increase efficiency in internal operations. With the ability to mix between the search data and model language (LLM) brings the groundbreaking solution from the system faq advanced to automate content, support customer service. Not to be left behind, the businesses need to proactively capture, deployment of modern technologies such as RAG to open up opportunities for sustainable development, enhance operational efficiency in the future.<\/span><\/p>\n<p><strong>CONTACT INFORMATION:<\/strong><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"text-align: justify;\" aria-level=\"1\">Lac Viet Computing Corporation<\/li>\n<li style=\"text-align: justify;\" aria-level=\"1\">Hotline: 0901 555 063 | (+84.28) 3842 3333<\/li>\n<li style=\"text-align: justify;\" aria-level=\"1\">Email: info@lacviet.vn \u2013 Website:\u00a0<a href=\"https:\/\/lacviet.vn\/en\/\">https:\/\/lacviet.vn<\/a><\/li>\n<li style=\"text-align: justify;\" aria-level=\"1\">Headquarters: 23 Nguyen Thi Huynh, P. 8, Q. Phu Nhuan, Ho Chi Minh city<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Trong th\u1eddi \u0111\u1ea1i th\u00f4ng tin b\u00f9ng n\u1ed5, doanh nghi\u1ec7p \u0111ang \u0111\u1ed1i m\u1eb7t v\u1edbi m\u1ed9t kh\u1ed1i l\u01b0\u1ee3ng d\u1eef li\u1ec7u ng\u00e0y c\u00e0ng l\u1edbn tr\u1ea3i d\u00e0i t\u1eeb n\u1ed9i b\u1ed9 \u0111\u1ebfn d\u1eef li\u1ec7u kh\u00e1ch h\u00e0ng, th\u1ecb tr\u01b0\u1eddng. V\u1eady l\u00e0m th\u1ebf n\u00e0o \u0111\u1ec3 doanh nghi\u1ec7p v\u1eeba t\u1eadn d\u1ee5ng \u0111\u01b0\u1ee3c l\u01b0\u1ee3ng d\u1eef li\u1ec7u kh\u1ed5ng l\u1ed3 v\u1eeba t\u1ed1i \u01b0u h\u00f3a c\u00e1c quy [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":42830,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[99],"tags":[79],"class_list":["post-41927","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-du-lieu-va-ai","tag-thuat-ngu-ai"],"_links":{"self":[{"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/posts\/41927","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/comments?post=41927"}],"version-history":[{"count":12,"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/posts\/41927\/revisions"}],"predecessor-version":[{"id":46727,"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/posts\/41927\/revisions\/46727"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/media\/42830"}],"wp:attachment":[{"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/media?parent=41927"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/categories?post=41927"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lacviet.vn\/en\/wp-json\/wp\/v2\/tags?post=41927"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}