What is RAG? RAG Application Software Development Services

Have you ever wondered how chatbots can answer complex questions accurately and align with the “brand personality”? The secret lies in RAG (Retrieval-Augmented Generation) technology. So, what is RAG? How does this technology work, and how can Aegona leverage RAG to benefit businesses in Vietnam and globally? Let’s explore this in the article.

What is RAG? 

How does it work? Retrieval-Augmented Generation (RAG) is a technique that enhances the performance of Large Language Models (LLMs) by integrating data from external sources. This process includes the following steps:

1. External data preparation

External data refers to information not included in the original LLM dataset. It is gathered from various sources through API connections to platforms, databases, or text documents. Once collected, the data is converted into numerical representations via language embedding models, creating a knowledge base that the LLM can retrieve at any time.

2. Retrieving relevant information

When a user inputs a query, it is converted into a vector format and matched against the knowledge base. For example, if the system needs to provide information on leave policies, it will search relevant documents and the employee's leave history. The relevance of the information is determined by vector calculations.

3. Enhancing LLM through prompting

Once relevant information is found, RAG integrates that data into the LLM as a prompt, enabling the LLM to generate a more accurate response. Natural language processing techniques are used to optimize communication between the data and the LLM, ensuring that responses are understandable and user-friendly.

4. Continuously updating external data

To keep the information accurate and relevant to market and business developments, external data needs to be regularly updated. This can be done through real-time or periodic data collection and backup settings.

Benefits of applying RAG technology for optimized information retrieval

1. Enhancing user trust

RAG helps LLMs provide accurate information with clear source references. The results may include citations or links to original documents. This allows users to verify and explore further, reinforcing trust in the information provided.

2. Flexible and easily adjustable information retrieval

With RAG technology, companies like Aegona can upgrade mobile apps, websites, and software using AI chatbots more effectively. Moreover, these data sources can be updated and adjusted to match changes in business operations.

3. Data security and access control

RAG helps businesses manage access to various information levels more securely. The system can set responses according to different user roles, such as user, moderator, editor, or admin. This ensures data security according to each role's access requirements within the organization.

For Example: To help visualize the value and function of RAG technology, consider the following example. Imagine your company distributes beverages. You use an ERP system to track orders, customer requests, customer feedback, sales, customer information storage, and tracking of sales employees in the field. By applying RAG techniques to enhance the AI Chatbot's retrieval capabilities, you can gain the following benefits:

• As a sales employee, you might ask: "Which products does [Customer Name] prefer?", "Which soft drinks are on promotion in September?", or "Which products need a sales push in September?"
• As a sales manager, you could inquire: "Which sales employees performed best in September?", "Who in my sales team achieved their KPIs?", "What was the company’s sales for the previous month?", or "[Salesperson Name] is currently located where?"
• As a customer service employee, you could ask: "What is [Customer Name]'s purchase history?" or "What is the compensation policy for [Damaged package affecting product quality]?"
• As a marketing employee, you might ask: "What were the sales figures for product ABC during [time period]?", "Which product is the best seller?", or "Which product is experiencing a sudden surge in orders?"

Thus, by applying RAG technology to optimize GenAI for enterprise systems, you can have a talented assistant available 24/7 to provide accurate responses since this assistant is linked to enterprise data sources, enabling it to provide quick and precise information, helping reduce time-consuming manual tasks.

>> Read more: 

• Sales Technology Trends 2024: Integrating AI into CRM software
• How Much Is The Cost Of Mobile App Development In Vietnam?

Aegona – custom software development company in Vietnam

Although Aegona focuses on offering custom software solutions and professional website design, we do not provide RAG services like creating and updating external data sources for LLM, training LLM responses, or setting retrieval prompts, developing GenAI, etc. However, we collaborate with reputable partners in this field to deliver modern, efficient, and performance-oriented software solutions.

If you are interested in custom software development services or wish to explore partnership opportunities, please contact us via Phone/Whatsapp: (+84) 914 518 869.

AEGONA LTD - IT SERVICE & SOFTWARE DEVELOPMENT
Email: [email protected]
Phone: Office: (+84) 28 7109 2939. Hotline: (+84) 91 451 8869 | (+84) 83 940 5469
WhatsApp: (+84) 91 451 8869 
Website: www.aegona.com, www.aegona.vn
Address: Orbital Building (QTSC Building 9), Quang Trung Software City, District 12, Ho Chi Minh city, Vietnam.