Below you will find NoCode StartUp's Supabase course for beginners, make the most of the power of Supabase with FlutterFlow
What is Supabase?
Supabase is a Baas (Backend As a Service), a no-code application development platform that allows you to create complete web and mobile applications using just a visual interface, without the need to write code.
Supabase offers a wide range of features such as user authentication, real-time data storage, integration with external APIs, and more. With Supabase, you can create powerful, custom applications without needing to be an experienced developer.
What type of database does Supabase use?
Supabase uses a PostgreSQL database.
PostgreSQL is an open source and highly reliable relational database management system. It offers advanced features such as ACID (Atomicity, Consistency, Isolation, and Durability) support, complex queries, indexes, triggers, and more.
Supabase leverages the robustness and flexibility of PostgreSQL to provide a powerful database for developers to build their applications.
What can we build with supabase and FlutterFlow
Supabase is a versatile tool that can be used for a wide variety of projects. Here are some examples of projects that can be built with Supabase:
Task management apps: You can create a task management app where users can create, update, and delete tasks.
Ecommerce Applications: With Supabase, you can create an ecommerce application where users can browse products, add items to their cart, and place orders. Supabase can be used to store product information, order details and manage user authentication.
Social media apps: You can build a social media app where users can create profiles, post updates, follow other users, and interact with content. Supabase can be used to store profile information, posts, and manage user authentication.
These are just a few examples, but the possibilities are endless! Supabase offers database, authentication, and file storage capabilities, allowing you to create a wide variety of applications.
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.
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?
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.
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
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 theN8N Course – NoCode Startup and start transforming your company with artificial intelligence!
Artificial intelligence (AI) is transforming the way companies capture leads, interact with customers, drive sales and, consequently, close contacts. Its application offers numerous advantages, simplifying tasks in various areas of a business and promoting increasingly efficient management.
But how can you use AI for sales strategically? With the right tools, you can automate processes, personalize interactions, and improve your team’s sales performance, even without advanced technical knowledge. In this article, we’ll explore how to integrate AI into your business to generate scalable results and close deals every month.
Understanding the Impact of AI for Sales
The application of AI to sales has significantly transformed the way companies manage their sales operations. By automating operational tasks and offering optimized solutions, AI improves service agility and accuracy in critical processes, such as lead capture and qualification.
Furthermore, with smart tools, sales teams can meet customer demands in a more structured manner. As a result, they provide a more positive and efficient experience.
It has already been proven that companies that use AI in their sales strategies have seen significant increases in their results. According to research by Harvard Business Review, implementing AI can increase leads by more than 50%, reduce call times by between 60% and 70%, and reduce operational costs by between 40% and 60%.
Therefore, the impact of AI on sales goes far beyond simplifying tasks; it offers consistency in results, becoming an indispensable ally for companies that want to compete in an increasingly dynamic market.
Benefits of using AI for sales
Customer Interaction and Lead Management
AI chatbots provide personalized support 24/7, answering questions, qualifying leads, and collecting information. AI also segments leads and prioritizes those most likely to convert, optimizing team time and increasing campaign efficiency.
Team management and performance analysis
AI also benefits the internal team, analyzing the individual performance of each salesperson and identifying strengths and weaknesses to offer personalized training.
Consumer behavior analysis and data collection
With AI for sales, you can analyze your customers’ buying journey, identify trends and consumption patterns. As a result, you can offer personalized interactions based on each customer’s history and preferences, increasing satisfaction and the chances of conversion.
Sales training and task automation
AI personalizes team training with content and exercises tailored to each salesperson’s needs. This makes it possible to automate repetitive tasks, such as qualifying leads, sending emails, and generating reports, freeing up time for managers and teams to focus on more strategic activities.
Reduction of operational costs
By automating processes and minimizing errors, AI contributes to more efficient resource management, reducing waste and operational costs such as time spent on manual tasks, rework costs and unnecessary administrative expenses.
How to implement AI for sales in your business
1. Identify the main challenges
Before adopting any solution, map out the biggest challenges in your sales process. Do you need to optimize customer service, qualify leads, or automate tasks manuals? By mapping these challenges, it will be easier to direct your efforts, prioritize more critical areas and invest in tools that truly meet your business needs.
2. Choose suitable tools
Currently, the market offers several AI tools for sales, from chatbots for automated customer service to intelligent CRMs that analyze data in real time. Evaluate the available options and prioritize those that best meet the specific needs of your business.
3. Integrate the solutions into your system
Integration with systems such as CRMs (Customer Relationship Management), marketing automation and systems of business management (ERP), it is essential to ensure that AI tools work efficiently alongside existing platforms. Make sure data is connected and accessible to maximize benefits.
4. Train your team
With the training of a good team, artificial intelligence becomes less susceptible to making mistakes, since inconsistencies can be identified and dealt with in a more humane way.
Train your team to use AI tools effectively to interpret the information they generate. Your sales team will then be prepared to take full advantage of the potential of AI for sales.
5. Measure and optimize results
Finally, there’s no point in implementing AI without monitoring and adjusting processes. Monitor key performance indicators (KPIs) to assess the impact of AI on sales. Analyze results regularly and be ready to make adjustments when necessary to further improve results.
Implementing AI for sales doesn’t have to be a complicated process, especially with so many affordable solutions available. Start with small integrations and scale up as you see results.
AI for Sales: Create Automated Processes Using NoCode Tools
Creating automated sales processes with AI has never been more accessible, thanks to NoCode tools. Platforms like Make (formerly Integromat), Bubble, and FlutterFlow allow companies to configure intelligent solutions without needing programming knowledge.
With these tools, it is possible to customize processes, integrate systems and improve the operational efficiency of the sales team. Furthermore, AI Agent Manager Training from NoCode offers practical knowledge for those who want to implement robust AI solutions, maximizing results and simplifying the commercial routine.
By combining NoCode tools with specialized training, your company can transform the sales process once and for all, ensuring high performance and closing the best contracts in the digital market.
Conclusion
It is now clear that adopting AI for sales is not only a matter of efficiency, but also of competitiveness in an increasingly dynamic market. Start exploring the possibilities that this technology offers now! Transform your sales process to meet the needs of your Marketing and Sales team.
Want to learn more about how to implement these solutions? Visit the website NoCode Startup and discover courses, tools and tutorials that will boost your company's results!
THE Artificial Intelligence (AI) has transformed many industries, and video creation is no exception. AI tools for video are capable of automate processes, simplify editing while improving the final quality of audiovisual content. For content creators, marketers, and businesses, these technologies are powerful allies in optimizing video production and distribution. In this article, we explore how AI tools for video are changing the industry and highlight some of the best options available on the market.
Simplified automation and editing
One of the biggest advantages of AI tools for video is the ability to automate tasks that would otherwise be time-consuming and technical. For example, many AI tools offer the possibility to automatically cut, organize and even improve the quality of the video. Platforms such as Magist it's the Adobe Sensei use AI to identify the best scenes, adjust brightness and contrast, add subtitles and even apply visual effects, without the need for manual intervention. This makes it easier for creators who want to deliver high-quality content, but with less effort and in a shorter time.
AI Tools for Video: Benefits for Content Creators
AI tools for video bring significant benefits to content creators, especially in reducing production time. With AI, video editing, which used to be a complex technical process, becomes more accessible to anyone, regardless of their experience. Tools like Runway ML and Pictory They offer automatic edits, visual effects, and even data-driven suggestions for improvements, allowing creators to focus more on creativity and less on the technical process. In addition, these tools also make customization easier, allowing videos to be adapted for different platforms and audiences.
Enhanced experiences with artificial intelligence
With artificial intelligence, viewers’ experiences are more dynamic and immersive. Tools like Runway ML and Synthesia allow the creation of videos with innovative visual effects and digital avatars, creating a more engaging and personalized experience for the audience.
AI can also analyze viewer behavior and suggest content adjustments to maximize engagement. This results in more engaging videos with greater viral potential, as well as a superior viewing experience.
AI as an ally in digital marketing
In the context of digital marketing, AI has proven to be a powerful ally, especially when it comes to videos. AI tools for video allow you to create more effective campaigns, with personalized content for different audience segments. Synthesia, for example, offers the creation of videos with digital avatars, which makes it easier to personalize messages and create content in multiple languages, without the need for traditional recordings.
Already the Pictory is ideal for transforming articles and blogs into short, engaging videos for social media, optimized to increase reach and engagement. These tools help brands create content more efficiently, cost-effectively, and with a higher return on investment.
AI Tools for Video: Unlimited Potential with AI
The potential of AI tools for video is almost limitless. Artificial intelligence technology is constantly evolving, and new features are being released all the time. Tools like Runway ML, Synthesia and Pictory These are just the tip of the iceberg of what AI can offer. In addition to automated editing and personalization, AI can generate interactive videos, analyze engagement data, and even predict which types of videos are most likely to go viral. As these tools become more advanced, the power of video creation will expand, allowing anyone from beginners to professionals to produce high-quality content faster and at a lower cost.
Conclusion
AI tools for video are revolutionizing the way we create and consume audiovisual content. They offer a range of benefits, from process automation from editing to creating immersive, personalized viewing experiences. For content creators, businesses, and marketers, AI is a strategic ally that can save time and resources while maximizing the effectiveness of videos. As technology continues to evolve, the potential of AI tools for video will expand, opening up exciting new opportunities for the future of video production.
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