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What is RAG – IA Dictionary

Blog Cover 03 How to make an AI Agent trained with my RAG V3 data

Imagine you have a super-intelligent assistant trained based on all the knowledge available on the internet. However, when it comes to information specific to your business, it may not have direct references. So, how do you overcome this limitation?

One of the most effective ways to improve your assistant's intelligence is to train it with custom data, such as documents, articles, and internal files. 

This technique is known as RAG (Retrieval-Augmented Generation) and allows AI assistants to combine pre-existing knowledge with specific information to provide more accurate and useful answers.

Continue reading to better understand how this approach can transform the use of AI in your business.

How does RAG (Retrieval-Augmented Generation) work?

How does RAG work?

Now that we understand the concept of RAG (Retrieval-Augmented Generation), let's explore how it works in detail. 

Unlike traditional AI assistants that simply generate answers based on previously trained knowledge, RAG searches for information from external sources and combines that data with its prior knowledge to provide more accurate and relevant answers. 

The process can be divided into three main steps:

Ask the AI model

The user asks the AI assistant a question, just as they would in ChatGPT or another traditional chatbot.

Information Search (Retrieval)

The AI assistant queries a specific database, such as PDFs, websites, internal documents, or a business knowledge base. It retrieves the most relevant information to answer the question.

Augmented Generation

With the data retrieved, AI refines and structures the response by combining information from the knowledge base with its own linguistic model. This ensures a contextualized, accurate and relevant response.

This method is highly efficient as it allows AI to provide more personalized responses based on internal data. Additionally, the technology can leverage product documentation, support knowledge bases, and even company policies to ensure accurate and relevant information.

how does rag generation increase work

However, unlike a conventional chatbot, which responds based only on its original training, a RAG model can be constantly updated with new information, without the need for massive retraining.

In other words, this allows the AI to be highly dynamic and evolve progressively as new content is added, ensuring greater accuracy and relevance in responses.

For example, within the NoCode community, we provide assistants that use RAG to answer questions about tools such as make up, Diff, N8N and Bubble.

Furthermore, these assistants have been trained with specific documentation for these platforms, which allows them to provide even more detailed and accurate answers to students, thus facilitating learning and resolving technical queries.

5 Benefits of using RAG

Benefits of using RAG

Now that you understand how RAG works, let's explore the main benefits that this technology can bring to companies and users:

1. More accurate and contextualized responses

RAG enables AI assistants to query up-to-date information in real time, making responses more relevant and detailed.

2. Automation and efficiency

With the ability to access specific knowledge bases, AI reduces the need for constant human support, optimizing time and resources.

3. Continuous learning without the need for retraining

Unlike traditional AI models, which need to be constantly trained and retrained to learn new information, RAG can simply query updated databases.

4. Customization for different businesses

Companies can tailor AI to answer industry-specific questions by training the assistant with technical manuals, internal knowledge bases, and other relevant documents.

5. Applying RAG in customer support

In addition to academic and educational use, companies across a variety of sectors are using RAG to improve customer support.

Imagine a technology company that sells complex softwares. Customers frequently contact support with questions about specific features. 

With an AI assistant trained with RAG, a company can feed the AI with its internal knowledge base, technical manuals, and FAQs. This allows the agent to answer questions accurately and quickly, helping to reduce the need for human intervention and streamline customer support.

How to apply RAG in your business?

Companies from different segments can take advantage of this technology to improve internal processes, customer service and task automation. Below, check out some practical strategies for applying RAG to your business.

1. Identify your company's main needs

Before integrating RAG, evaluate which areas of your business can benefit from this technology. Ask yourself the following questions: 

  • Does customer support receive a lot of repetitive questions?
  • Does your team need to access technical documents frequently?
  • Is there a large database that could be better utilized?
  • Could internal training be optimized with an AI assistant?

2. Choose the right data sources

The great advantage of RAG is its ability to search for information from external sources. To ensure accurate and reliable answers, it is essential to select the best data repositories. Some options include:

  • technical documentation and product manuals;
  • FAQs and internal knowledge bases;
  • articles, research and case studies;
  • structured data from CRMS and ERPS;
  • pdf files, spreadsheets and notion.

3. Integrate RAG with your existing tools

For best results, RAG should be connected to the platforms your team already uses. Some ways to integrate include:

  • Chatbots and virtual assistants: AI trained to answer recurring questions and provide technical support;
  • Management systems (CRM/ERP): AI can access customer data to provide more personalized responses;
  • E-learning and corporate training: intelligent assistants that help employees access learning materials quickly;
  • E-commerce and customer service: chatbots that check inventory, return policies and product recommendations.

4. Evaluate and optimize 

Implementing RAG doesn’t end with the initial setup. It’s essential to monitor AI performance by analyzing metrics such as:

  • response accuracy rate;
  • user satisfaction;
  • reduction of service time;
  • most frequently asked questions and opportunities for improvement.

With this information, you can improve the AI database and ensure that the answers become increasingly accurate.

Conclusion

Whether it’s to improve customer support, automate processes or optimize internal knowledge management, RAG is a powerful and affordable solution for companies in different segments. 

With this technology, AI agents can access specific knowledge bases, improve the user experience and reduce the need for extensive training.

If you want to learn how to create intelligent AI assistants using N8N, check out NoCode Startup's complete course. In it, you will have access to practical training on automation and data integration to make your business' AI even more efficient.

Explore more about the N8N Course – NoCode Startup and start transforming your company with artificial intelligence! 

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Matheus Castelo

Known as “Castelo”, he discovered the power of No-Code when he created his first startup entirely without programming – and that changed everything. Inspired by this experience, he combined his passion for teaching with the No-Code universe, helping thousands of people create their own technologies. Recognized for his engaging teaching style, he was awarded Educator of the Year by the FlutterFlow tool and became an official Ambassador for the platform. Today, his focus is on creating applications, SaaS and AI agents using the best No-Code tools, empowering people to innovate without technical barriers.

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Artificial intelligence (AI) is no longer a distant promise. It is already transforming the way solo lawyers and small law firms operate. With affordable tools, it is possible to automate repetitive tasks and focus on what really matters: winning more clients and delivering high-quality service. AI agent for lawyer is the key to this revolution, offering practical solutions to everyday challenges. Each AI agent for lawyers acts as a virtual legal assistant, ready to optimize your routine.

What is an AI Agent and How Can It Help Independent Lawyers?

One AI agent for lawyer is an automated system that performs specific tasks on its own, based on predefined commands and machine learning. For lawyers, this means:

  • Reduction of time spent on manual and bureaucratic tasks.
  • 24/7 support with virtual assistants who answer common questions.
  • Greater productivity, with a focus on strategic activities.
  • Possibility of customizing legal flows according to the area of activity.

These agents can be integrated with various systems and platforms, enabling everything from the automatic drafting of contracts to the management of deadlines and hearings. In addition, they allow for the analysis of documents with greater speed and precision, reducing errors and rework. The great advantage is that, with no-code tools such as Agents with OpenAI Course and Free Dify Course, any lawyer can create their own AI agents without having to program.

Lawyer using AI agent to automate legal tasks in the office

Real Examples of Legal Automation with AI Agents for Lawyers

1. Automatic Generation of Petitions and Contracts

With tools like make up integrated into the Google Docs, it is possible to automate the creation of petitions. Imagine filling out a form and having the document ready in minutes.

2. Personalized Legal AI Agents

Much more than a simple chatbot, a AI agent for lawyer is able to continually learn from interactions, refining its responses and becoming more effective over time. Using ChatGPT integrated into the Dify, you can create an agent who not only answers common questions about labor rights or procedural deadlines, but also identifies service patterns and suggests improvements in responses. This agent can be trained with data from your own office, offering a highly personalized and efficient service, constantly evolving according to your client's needs.

3. Review and Analysis of Legal Documents

AI tools allow you to perform automatic readings, generate summaries and highlight important points in contracts and processes.

Legal document automation with AI agent assisting lawyers

AI Solutions for Lawyers: What You Need to Know

  • Dify: Creates tailor-made legal assistants.
  • make up: Automates service flows and document generation.
  • Agents with OpenAI: Develop custom agents for specific tasks.
  • N8N Course: Powerful tool for creating complex legal automation flows.

Relevant Tools in the Lawyer AI Agent Market

Document Review and Analysis

  • Kira Systems – extracts and analyzes complex contracts.
  • Luminance – automated review with AI, used in due diligence.
  • LegalSifter – reviews contracts and suggests improvements based on AI.

Automated Legal Research

  • JusIA – legal questions, analyze references and create document
  • LegalAI – write objections, initial petition with AI.
  • CaseText – AI-powered legal research (English).
  • LexisNexis – global AI-powered legal research platform.
  • Westlaw – advanced legal research, powered by AI.

Legal Document Automation

  • LawGeex – automatically reviews contracts, with AI.
  • DocuSign CLM – complete automation of contracts.

Legal Chatbots and Customer Service

  • DoNotPay – chatbot that solves simple legal questions (English).
  • IBM Watson Legal – AI solutions and chatbots for the legal sector.

Office and Process Management

  • ProJuris – Brazilian legal software with AI and automation.
  • Advbox – automation of flows and digital legal management.

Predictive Analysis and Jurimetrics

Law Firm Integrated AI Agent Workflow

Building an AI Legal Agent Using N8N and Dify

To create a more robust lawyer AI agent, you can integrate the N8N, Dify and ChatGPT. Check out this guide:

  1. Map Your Office's Needs: Define what functions the bot needs to have: answer questions, send documents, schedule appointments.
  2. Create FAQs and Flows: List frequently asked questions and response paths. In Agents with OpenAI Course you learn how to model these flows.
  3. Configure Dify: In the dashboard, create your bot based on the questions and answers, adjusting the behavior.
  4. Use N8N for Integration: Connect Dify to other platforms like WhatsApp, Google Calendar or Docs. In N8N Course you learn how to create these integrations.
  5. Automate Repetitive Tasks: Use N8N to trigger automatic responses, save data, and send alerts.
  6. Test and Improve: Put the bot into action, collect customer feedback, and optimize the system.

With this integration, your legal chatbot will not only answer questions, but also perform automatic tasks, increasing your level of service and productivity.

Will AI Replace Lawyers? No, But It Will Replace Those Who Don’t Use AI

Artificial intelligence is here to be an ally, not a replacement. Today, thousands of lawyers are already using AI agents to optimize their day-to-day activities. Each AI agent for lawyers is designed to assist in specific legal tasks, without replacing human critical reasoning and strategy. For example, law firms are automating the generation of standard contracts, reducing document production time by up to 70%. Lawyers are also using AI agents for lawyers to review large volumes of documents in due diligence processes, finding critical information in minutes. In addition, legal chatbots, such as AI agents for lawyers, allow you to serve customers 24/7, answering simple questions and directing them to specialized assistance when necessary.

Learn How to Create Your Own AI Agents and Multiply Your Results

Want to master these tools and transform your office?

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Further Reading:

Do you still waste hours reading long articles, emails or documents? Artificial Intelligence (AI) can do it for you in seconds. AI tools AI to summarize texts are revolutionizing the way we study, work and produce content. With the advancement of technology, it has become possible to delegate the reading and synthesis of large volumes of information to intelligent systems, allowing you to focus on what really matters: making decisions based on accurate and relevant information.

In this article, you will discover how to summarize texts with AI, what are the best tools, practical examples and how to automate this task with no-code platforms, even if you don't have advanced technical knowledge.

Introduction to using AI to summarize texts

Recommended Reading

What is an AI for Text Summarization?

Imagine having to read a document that is dozens of pages long and needing to capture the essentials in just a few minutes. This is exactly where summary AIs come in. They are like those attentive coworkers who know exactly what to filter out in a sea of information. With each paragraph you read, these digital assistants separate the essential from the accessory, creating a summary that makes sense to you. And the best part is that they do this with the naturalness of someone who understands our way of thinking, highlighting precisely what is worth reading. This makes our routine easier, more productive and organized.

The use of AI allows for greater efficiency when dealing with long texts, providing a more dynamic and optimized reading experience. And the best part is that you can shape these tools to your liking: it’s as if you were teaching the AI to speak your language and that of your audience. Do you want a more direct summary for executives? Or something more detailed for students? With small adjustments to the settings, it’s as if you were giving personalized instructions to an assistant that understands exactly what you want.

What Types of Text Can AI Summarize Well?

  • Articles and blog posts
  • Corporate reports and emails
  • Meeting or video transcripts
  • PDFs and academic documents

These are just a few examples. AI can also work with texts in different languages, respecting cultural and linguistic contexts. This makes it a valuable tool in international corporate environments and academic institutions.

Top AI Tools for Text Summarization


ChatGPT

ChatGPT can be used with custom prompts or plugins to generate summaries with different styles and levels of detail. For example, you can configure a prompt to summarize academic articles into bullet points, adapt corporate reports to more objective language, or even generate executive summaries from meeting minutes. Additionally, with memory functionality or API integration, ChatGPT can be incorporated into automated workflows where it learns from feedback and adjustments, making each summary more aligned to your needs.

QuillBot

QuillBot offers a dedicated tool for summarizing sentences or paragraphs, ideal for academic texts and articles. It also allows you to adjust the level of detail in your summary, which is great for those who need a quick overview or a more in-depth summary. QuillBot also includes additional features such as paraphrasing and a grammar checker, which makes it an even more complete tool for those who work with large volumes of text.

SMMRY

SMMRY is a simple, online solution that focuses on condensing texts into a few user-adjustable sentences. What sets this tool apart is its minimalist approach, ideal for those who need a quick, straight-to-the-point summary. You can control the number of sentences you want in the final result and adapt the tool to remove specific sentences, such as those containing certain keywords or quotes.

Resoomer

Resoomer is designed for argumentative and academic texts, with support for multiple languages. The tool is especially useful for those who need to analyze long texts with a clear logical structure, such as essays, dissertations, and legal articles. Resoomer allows you to quickly identify the main arguments, central ideas, and conclusions, making dense texts easier to understand. In addition, it offers browser integration to summarize web content in real time, which is a benefit for researchers and students.

Scholarcy

Scholarcy makes it easy to summarize scientific articles and also generates keywords and study sheets. This tool is especially effective for those who work with academic publications, as it not only condenses the content but also highlights important sections such as objectives, methodology, results and conclusions. Scholarcy also allows the extraction of tables, figures and references, organizing this information in a quick-read format. Integration with reference managers such as EndNote and Zotero is a plus for researchers.

Zamzar Summarizer

Zamzar Summarizer allows you to convert and summarize files such as PDF and DOCX in a simple and straightforward way. The great advantage of Zamzar is its ability to handle a wide variety of file formats, offering not only text summarization but also conversion between formats such as TXT, HTML, and EPUB. This makes it ideal for professionals who deal with documents on different platforms and need to integrate them into a single digital workflow. In addition, the tool can be used without the need for installation, directly from the browser, which further speeds up the process.

Notion AI

Notion AI is ideal for Notion users, making it easy to summarize documents and take notes within the app itself. In addition to summarizing text, Notion AI also allows you to rewrite paragraphs, generate headings, and create lists from text content. Integrated directly with your pages and databases, Notion AI streamlines the workflow for teams using the platform to manage projects, documentation, and ideas.

Automating summaries with AI and no-code platforms

Automating Summaries with AI and No-Code

Use AI to summarize texts goes far beyond manual tools. By combining no-code platforms like Make with robust AI, you can completely automate the process. Imagine you receive an email with a long document, and the system automatically summarizes the content and saves it to your cloud. This is productivity with AI applied intelligently.

Practical Example

“How I Built an Automatic Email Summarizer with Make + OpenAI”

In this example, you will learn step by step how to set up this automation. First, we define a trigger in Make to detect new emails with attachments. Then, we connect the flow to the OpenAI API, which processes the text and generates a summary. Finally, the summary is sent to your email or saved in a Google Doc. This solution is ideal for those who receive a lot of reports or proposals and need to evaluate them quickly.

Another interesting approach is to create a custom agent using the N8N it's the ChatGPT. With N8N, you can create more complex and adaptable workflows. For example, you can set up a workflow where the system automatically processes, via API, the documents you send to a Google Drive folder, summarizes them and classifies them by topic in spreadsheets. The agent learns from the edits the user makes, identifies text types and adjusts the summary style according to the topic, becoming more efficient with each interaction.

For those who want to create robust automations with N8N, check out our N8N Course.

Practical tips for improving results with AI

Practical Tips to Improve Your Results with AI

If you are just starting to use AI to summarize texts, some good practices can make all the difference:

  • Adjust the prompts: If the AI doesn’t deliver exactly what you want, refine your instruction.
  • Test different tools: Not all AIs respond the same way. Explore and see which one works best for you.
  • Automate when possible: Use no-code tools to create flows that save you time.
  • Review summaries: Even with AI, reviewing ensures that the content is aligned with your needs.

Let's clear up your doubts?

If you still have questions about how to apply AI to summarize texts, here are some answers that may help:

What are the best AI options? to create summaries? Many users use tools like ChatGPT, QuillBot and SMMRY for their practicality and the efficient results they offer. Depending on the volume and type of text, you may want to opt for a more automated solution, such as integration with Make.

Can I automatically summarize long texts? Yes! Using AI to summarize text in conjunction with automation platforms, you can set up systems that process long documents automatically.

How to ensure that the summary is unique? Personalize prompts and always review content. While AI rewrites, human adjustments add value and avoid originality issues.
With AI, you can transform the way you deal with information on a daily basis. From automating email summaries to creating complete workflows, the possibilities are endless. Integrating these tools into your daily routine is the first step to saving time, increasing productivity, and standing out professionally.

Want to master AI automation? Get started with our Makeup Course it's the Agents Course with OpenAI.

Artificial intelligence (AI) is causing profound transformations in several sectors, and education is one of the fields most impacted. From personalized classrooms to automated assessment systems, the use of AI artificial intelligence in education has been gaining increasing prominence. As a result, the impact of AI in schools is reshaping the way teachers teach and students learn, promoting a true digital transformation in education.

In this article, you will understand how AI is being applied in education, what the main tools are, the benefits (and challenges) of this revolution and how to prepare for this new scenario.

Recommended readings for further study:

Application of artificial intelligence in the classroom

What is Artificial Intelligence and how does it connect to education?

Artificial Intelligence is a field of computing that seeks to develop machines capable of learning, reasoning and making decisions. In the educational context, it is applied to personalize learning, automate administrative processes and offer more dynamic and inclusive teaching experiences.

The applications of artificial intelligence in education They range from smart tutors to platforms that automatically correct tests or create lesson plans based on each student's needs.

Practical applications of AI in the classroom

Artificial intelligence is no longer a distant promise and has become an integral part of contemporary educational reality. Instead of waiting for an uncertain future, teachers and students are already using AI-based technologies in a wide range of school activities. This transformation is happening quietly but with great impact — and best of all, with accessible tools that do not require advanced technical knowledge.

Next, we will explore how this presence of AI is realized in everyday education. More than presenting platform names, the goal is to reveal practical possibilities, demonstrate how each resource can be inserted into pedagogical dynamics and, most importantly, encourage educators to begin their journey with AI — even if it is with small steps. After all, each tool presented here can be the starting point for a profound transformation in the way we teach and learn.

1. Adaptive learning platforms

Solutions like Khan Academy with AI from OpenAI offer personalized learning paths based on student performance, adjusting content in real time.

2. Auto-correction and smart feedback

Platforms like Gradescope and Socrative use AI to correct objective tests and offer detailed performance analysis, saving educators time.

Additionally, you can create automated correction flows using Make integrated with Google Docs or Notion, allowing you to deliver activities with personalized feedback.

3. Virtual Assistants and AI Tutors

Tools like ChatGPT, Google Bard and Khanmigo are used by students to clarify doubts and reinforce content based on natural language.

Educators can also use Dify to create custom educational interfaces and subject- or skill-specific tutor bots.

4. Content creation with AI

Educators can use AI to generate quizzes, presentations, and even lesson plans with tools like AI-powered Canva, Notion AI, and ChatGPT, accelerating the preparation of teaching materials.

If you want to go a step further, you can use the Agents Course with OpenAI to create interactive educational experiences with full personalization of content and the student journey.

Further reading: The best Artificial Intelligence tools

Practical examples of the use of AI in education

Benefits of AI in Education

In addition to its growing presence, artificial intelligence in education offers significant advantages, such as:

  • Personalizing learning: each student learns at their own pace and style. As a result, it is possible to better meet individual needs.
  • Automation of repetitive tasks: more time for the teacher to focus on mediation and relationships. In addition, it reduces the wear and tear on operational processes.
  • Inclusion: Students with special needs benefit from features like auto-reading, captions, and real-time translation. On the other hand, it’s important to make sure these tools are accessible to everyone.
  • Engagement: More interactive and adaptive content increases student interest. This makes learning more engaging and effective.

Challenges and precautions in the use of AI

Despite the benefits, the use of AI in education also requires attention to points such as:

  • Student Data Privacy
  • Over-reliance on technology
  • Inequality of access to digital tools
  • Digital literacy for teachers

Therefore, it is essential that educators prepare themselves not only to use these tools, but also to deal with the impacts they can generate in the school environment.

How Educators Can Start Using AI

To start using the artificial intelligence in education, even without technical knowledge, teachers can explore AI in their daily lives with simple tools. Here are some initial ideas:

  • Try ChatGPT to generate questions, summaries or lesson plans.
  • Use Canva to create visuals with automatic suggestions.
  • Explore platforms like Khan Academy with AI to enrich teaching.

In addition to these options, it is possible to implement more robust solutions with no-code tools:

Furthermore, a practical way to advance is to train yourself with specific training. If you are an educator and want to master these technologies, also see the AI Agent and Automation Manager Training, where we teach how to use AI in practice, with a focus on productivity and automation in teaching.

Future of education with AI teacher interacting with dashboard

The Future of Education with AI

THE artificial intelligence in education It will not replace teachers, but it will be a powerful ally. The combination of the educator’s human perspective and the analytical capacity of AI can take teaching to a new level of personalization, scale and impact.

This movement represents a true digital transformation in schools, where technologies such as educational chatbots with AI, personalized tutors and pedagogical automation become part of everyday school life.

As more institutions adopt these tools, the difference will lie in how to use them ethically, creatively and strategically. To achieve this, ongoing training of education professionals will be essential.

Further reading:

Want to transform your educational practice with AI? Get started now with practical training, even if you've never programmed before: Discover our AI and NoCode course

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