How to create AI applications without knowing how to program

February 26, 2024
6 min

Estimated reading time: 9 minutes

Artificial intelligence tools (AI) are becoming increasingly present in people's daily lives. And why would this be different in the no code universe?

In truth, AI makes the work of programming in code even easier and faster. If you create an application with templates It was already a revolution, imagine creating it with just a text command. Or thinking about the future, imagine creating a complete and robust app with just a voice command.

It sounds like science fiction, but it's not. This reality is closer than you imagine! If you want to know how to create applications with AI and make your process even easier, you've come to the right place. In this content, you will learn what a no-code AI app is and how to create an app without knowing how to program.

At the end of the text, you will be ready to take the first steps in creating your AI app and stand out in the market. Good reading!

What is a no code AI app?
Why create an AI app without using code?
How to create an app without knowing how to program?
How to integrate AI into a no code app
Learn to program with No-Code!

What is a no code AI app?

A no-code AI app is the future of programming happening before our eyes. An AI application is one that uses artificial intelligence to perform some function, for example:

Voice recognition;
Image classification;
Demand forecast;
Chatbot;
Product recommendation.

A no-code AI app will include this same definition, with just one change: it will be created without using code. Instead, the app is built using no code or low code platforms, which allow you to develop applications in a visual and intuitive way, dragging and dropping elements onto the screen.

Why create an AI app without using code?

It was easy to understand what an AI no code app is, right? But you may be wondering why this is. After all, if programming in code is already so simple, why want to simplify it even more?

There are a few reasons for this, see:

Reduces launch time

To create a no-code app with the help of artificial intelligence, all you need is to write good commands. After the platform delivers the app, some fine adjustments will certainly be necessary, as the technology is still evolving.

But that It greatly reduces the time it would take to create an app. In other words, you can test your idea, validate your product and reach your audience more quickly, gaining a competitive advantage in the market.

Increases efficiency

Another advantage of creating a no-code app with the help of artificial intelligence is that you can increase your efficiency, both in creation and use. With the agility we explained above, it is possible to make adjustments and improvements to your app according to user feedback, without losing time or quality.

Reduces dependency on AI experts

Furthermore, by creating an app that has AI in its features, you can reduce dependence on experts in this area. These professionals are scarce and expensive on the market.

With AI tools that facilitate the integration of functions performed by intelligent algorithms, you can create your app without having to hire or consult these professionals, saving resources and avoiding bottlenecks.

Open customization options

Creating an AI app without using code also opens up customization options. You can adapt the app to your needs and preferences, without being limited to ready-made or standardized solutions. You can choose the AI functions that best suit your purpose.

Facilitates integration with other systems

Finally, another reason you should create AI apps with no-code tools is that it makes integration with other systems easier. That way, you can take advantage of AI in conjunction with other technologies, as cloud computing, big data, blockchain, etc.

How to create an app without knowing how to program?

You can already imagine the answer to this question, right?

To create an app without knowing how to program, you can use the no code and low code platforms, which facilitate the creation of applications in a visual and intuitive way, without having to write or edit lines of code.

If you want to know how to learn to program alone, continue reading!

There are several no code and low code platforms available on the market, each with its own characteristics, functionalities and prices. Some of the most popular are:

FlutterFlow

O FlutterFlow It is one of the most popular options on the market and also our recommendation. This platform allows the creation of native apps for iOS and Android.

It works with templates and you can create the app by dragging and dropping widgets on the screen. The difference when talking about artificial intelligence in FlutterFlow is Al Gen, the new tool that creates apps from texts.

With Al Gen, It is possible to develop a menu app for restaurants with just one sentence. Or even one that simulates other social networks, such as Instagram, Facebook and X (formerly Twitter).

Bubble

O Bubble is another no-code platform that creates web and mobile applications, using a graphical interface. With it, we also use the “drag and drop” model to organize the elements and define the app’s logic with visual workflows.

Bubble allows integration with AI functions, such as Synthesia AI. This tool uses artificial intelligence to create videos with anyone's face. Imagine making educational videos with the image of a superhero, for example. Or even Easter advertising videos using the bunny, the possibilities are endless.

Framer

Framer is also a no-code platform option aimed at creating UI and UX designs for any type of website. With it, you can even import Figma designs and use its tools to develop the layout.

The focus of this platform is help teams build better products and it does this through a system of collaboration and sharing of projects in real time. Framer lets you leave comments and respond feedbacks directly on the canvas.

Integration with other AI platforms is another possibility, just like the previous two tools.

Make Integromat

Unlike other iPaaS platforms, Make Integromat is intuitive and linear. With it, you can connect applications and design workflows in a simple way. Plus, it lets you manage content for your blog posts, job listings, and marketing pages with the built-in CMS.

If you want to know more about these platforms and become a no-code expert, access our complete training and discover the options! We have complete courses on FlutterFlow, Bubble, Framer and Make Integromat. Don't be left out!

How to integrate AI into a no code app

It is already clear how AI can bring numerous benefits to applications. Fortunately, with these tools we explained above and a lot of creativity, anyone can integrate AI into a app no code.

We have selected some of the most popular artificial intelligences and will show you in practice how their integration into apps code can be interesting for you. Continue reading!

ChatGPT

O ChatGPT is an artificial intelligence chatbot from the company OpenAI, which uses natural language processing (NLP). It is certainly the most famous AI to emerge in recent years and you can implement it in your app created in FlutterFlow.

You can, for example, create a conversation app with the chatbot for a company that sells beauty products. In it, you can configure answers related to frequently asked questions about the best-selling products. To do this, you need to integrate the app with the OpenAI ChatGPT API, using the FlutterFlow API widget.

Gemini

Gemini (formerly Bard) is an AI-assisted writing tool from Google that works with text commands. Now imagine integrating it into an app developed with Bubble.

You can create a creative writing app for writers in which the user types a command, such as “create a creative title for a text about AI” and receive an immediate suggestion. To do this, just use the Gemini plugin on Bubble.

Dall-e

Dall-e is among the best artificial intelligence tools current. It can create realistic and artistic images from a description. Its language model is the same as ChatGPT, but it is trained on a large dataset of text-image pairs.

Dall-e integration can be done with Framer, for example. You can develop an image generating website using these two tools.

Voiceflow

Voiceflow is a chatbot and voice assistant developer that creates great conversational experiences. Now, Think about what an integration between Voiceflow and Make Integromat would be like.

An example would be the creation of a chatbot aimed at hotel reservations. Voiceflow can listen and understand user requests. Then, send this data to Make Integromat and a workflow will be developed from there. Pretty cool huh?

Learn to program with No-Code!

Creating an AI application without knowing how to program is possible thanks to no-code platforms. So, if you want to learn more about these platforms and how to enter the programming market, No-Code Start-Up is the ideal place.

Enroll now in a course at code and start building your AI app today. Let's enjoy this wave of code together!

Also visit our Youtube channel

Learn how to create AI Applications, Agents and Automations without having to code

AI Software Development in the Financial Sector

Creating AI-based solutions in the financial context requires robustness, security, and adaptability. Developing this type of software requires an architecture that is prepared to handle large volumes of data, continuous learning, and the ability to provide accurate insights.

In addition, systems need to be able to handle sensitive data, integrate with multiple sources (such as banks, brokerages, and ERPs), and adapt quickly to regulatory changes in the industry. Flexibility and modularity are core elements of any AI architecture for finance.

Integration with Existing Infrastructures

Much of AI’s success in the financial sector depends on its integration with legacy systems. This includes internet banking platforms, CRMs, payment gateways, and compliance tools. Using NoCode platforms such as make up or N8N allows you to create effective connections without the complexity of traditional development.

By the way, if you want to experience in practice how to integrate financial flows with AI, No-Code Start-Up provides a free N8N course with full video on YouTube. It's a great opportunity to explore real automations and understand how to structure secure and intelligent integrations in an accessible way.

With this approach, banks and fintechs can activate intelligent flows based on real data, such as automatic sending of alerts, personalized segmentations and recommendations based on consumer behavior.

Challenges in AI Development for the Financial Sector

Despite the enormous potential, there are challenges that need to be considered. Among the most relevant are:

Data quality: models are only effective if fed by clean and organized data.
Explainability: It is essential to understand how the AI arrived at a particular recommendation.
Cultural resistance: Traditional teams may resist adopting automation and algorithm-based decisions.

As highlighted by Deloitte, the combination of data governance, team training and ethical monitoring of AI is essential to mitigate risks and generate consistent results.

Security and Regulatory Compliance

The financial sector is one of the most regulated in the world. Therefore, all AI applications must comply with standards such as LGPD, GDPR and Central Bank regulations.

The adoption of good practices Data Privacy by Design, end-to-end encryption and role-based access control are just some of the basic requirements. Platforms such as Xano offer robust infrastructure with a focus on security for those who want to develop financial backends with AI.

Digital security illustration with padlock and financial data, symbolizing protection and compliance in AI application

Software Scalability and Resilience

As AI becomes a critical part of operations, it is necessary to ensure that systems are scalable and resilient. This means being able to grow as demand dictates, without compromising performance or security. Cloud computing and the adoption of microservices are essential strategies in this journey.

Companies like Goldman Sachs and Bank of Brazil have already demonstrated, in different contexts, how AI models can be deployed gradually, safely testing hypotheses before scaling to the entire operation.

AI Agents for Finance: Use Cases and Applications in the Financial Sector

1. Automated credit analysis

Companies like Credits use AI to evaluate hundreds of variables — including banking history, spending habits, and public data — to offer personalized credit. This reduces default rates and expands access to credit in a fairer way. According to McKinsey, automation can reduce analysis time by up to 70%.

2. Fraud prevention

O Bradesco and other institutions have implemented machine learning models that detect fraud based on behavioral patterns. When a transaction deviates from the pattern, the system triggers an automatic block or sends an additional verification to the user. According to Visa, the use of artificial intelligence helps prevent fraud totaling approximately US$14T25 billion.

3. Automated investment management

Robo-advisors like the ones from XP Investments use algorithms that analyze investor profiles, financial goals and market conditions to assemble and rebalance portfolios autonomously. CB Insights highlights that these systems are democratizing access to quality financial services, previously restricted to large investors.

4. AI-powered customer service

O Itau has incorporated AI into its digital channels, allowing customers to renegotiate debts, request second copies of bills or consult invoices using natural language. This reduces response time, improves customer experience and frees up human teams for more complex cases. According to Accenture, up to 80% of first-level banking interactions can now be automated using artificial intelligence.

5. Cash flow forecast

Financial management startups use AI agents for finance that integrate data on accounts payable and receivable, seasonality and market trends to predict cash flow for the coming months with high accuracy. Based on this information, more assertive decisions can be made. Harvard Business Review reinforces that this approach reduces the margin of error in financial projections and improves strategic planning.

The Role of AI Agents for Finance

Among all the applications, the AI agents for finance stand out for their versatility and accessibility. They function as intelligent “copilots”, performing tasks such as:

Automatic generation of financial reports
Sending alerts about targets or deviations
Predictive profitability analysis

Using platforms such as Dify and OpenAI, it is possible to configure these agents with natural language, making them easier to use even for those without technical training. This expands access to data intelligence in the financial sector.

The Future of AI in the Financial Sector

Artificial intelligence in the financial sector is no longer a distant promise — it is present in strategic decisions, customer service, and risk management. The adoption of technologies like AI agents for finance represents a leap forward in digital maturity. As technical challenges are overcome and platforms become more accessible, companies of all sizes will be able to use AI not only to automate, but to evolve.

Organizations that master the use of AI ethically, safely, and strategically will be ahead in delivering value and conquering the market. The future of finance is predictive, integrated, and data-driven — and it starts now. Want to learn how to build your own AI-powered financial agents without coding? Access the AI Agent Manager Training and discover the most practical way to apply all this in your context.

May 13, 2025
5 min

Matheus Castelo

How AI is changing the market: challenges and opportunities

How AI is changing the market can be observed in practically all sectors of the economy, and this change is intensifying every day. Artificial intelligence (AI) is being recognized as a disruptive force that is profoundly reshaping the global market. From simple tasks to complex decisions, it has been integrated into processes in various sectors, transforming the way people work, consume and manage businesses.

Furthermore, when observing the effects of this transformation, it becomes clear how much the job market is being reconfigured: new opportunities arise, some professions lose ground and others adapt or are reborn with the support of technology, which demonstrates how AI is changing the market in a broad and profound way.

How AI is changing the job market

AI is accelerating the automation of repetitive and operational tasks. AI systems are already being used to efficiently perform:

Customer service with chatbots.
Predictive data analysis for sales and marketing.
Automated financial and audit processes.
Inventory control and logistics.

These changes not only reduce operational costs, they also require the workforce to be retrained for new roles, which reinforces how AI is changing the job market with great intensity.

Representation of people and artificial intelligence collaborating in different professions

Professions affected by artificial intelligence

According to PwC's report on the future of work (source), it is estimated that up to 30% of human tasks could be automated by the mid-2030s. This data shows, in practice, how AI is changing the job market and skills requirements.

Some of the roles most impacted by AI include:

Telemarketing operators
Administrative assistants
Data Analysts (some tasks being replaced by generative AI)

On the other hand, new functions emerge, such as:

Prompt Engineers
Automation experts with NoCode
Conversational Experience Designers
Intelligent Agent Managers

Those AI agents, for example, have been increasingly used in companies seeking to automate decisions and perform tasks with minimal human intervention. According to an analysis of the The Verge, large companies such as OpenAI, Google and DeepMind are investing heavily in the development of these systems, which can already act independently in complex corporate processes. They are designed to operate autonomously, learn continuously and integrate with other technologies — which makes them key players in the ongoing digital transformation.

What's Happening Now: How AI is Changing the Marketplace in Numbers

The AI market is experiencing exponential growth. The sector is estimated to surpass US$ 500 billion in value by 2027. There is a global race for innovation, with startups, large companies and governments investing heavily in:

Generative models (like ChatGPT)
Robotic Process Automation (RPA)
Artificial intelligence applied to health, education, law and agribusiness

This movement demonstrates how AI is being positioned as a strategic asset for growth and competitiveness.

What are the negative aspects of AI in the job market?

Despite promising advances, important challenges also arise:

Structural unemployment: functions terminated without sufficient time for requalification
Digital inequality: not everyone has access to technological education
Technological dependence: companies become hostages of platforms and algorithms
Ethical and privacy issues: inappropriate use of data and biased automated decisions

These factors require public policies, business leaders and civil society to debate limits, transparency and responsibilities in the use of technology.

People using AI tools in a modern workplace

Opportunities and the future of work with AI

The key is in the conscious adaptation. The future of work will be driven by:

Continuous learning and professional requalification
Mastery of AI tools and NoCode platforms
Creating new business models based on data and automation
Development and management of autonomous AI agents

Increasingly, professionals and companies will need to adopt a stance proactive and experimental, turning AI into an ally.

Recommended courses:

AI and entrepreneurship: new market frontiers

Artificial intelligence is not only transforming the traditional job market, it is also paving the way for new business models. Digital entrepreneurs are using AI to create scalable products such as intelligent assistants, recommendation systems, and data-driven SaaS platforms. No-code tools combined with AI agents are enabling the emergence of lean, highly automated, and highly personalized startups.

A great example is the AI-based micro-SaaS, which solve very specific problems and can be created by a single person. Platforms like Bubble, FlutterFlow and Make, integrated with OpenAI models, make this scenario not only possible, but accessible.

For those who wish to explore this new territory, we recommend SaaS IA NoCode Training, designed to transform ideas into digital products using the power of artificial intelligence.

How AI is changing the market and shaping the future

Artificial intelligence is changing the market in an irreversible way. It is not only a technological revolution, but also a social, professional and economic transformation. The question is no longer “if” AI will impact your work, but “how will you position yourself in this new era”.

The good news is that there have never been so many accessible tools for those who want to learn AI in practice.

See all No Code Start Up training and courses

May 6, 2025
4 min

Matheus Castelo

AI for Lawyers: Automate Legal Tasks Efficiently

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

Data Lawyer Insights – jurimetrics applied to Brazilian law.
Tech Preamble – predictive analysis and jurimetrics for lawyers.

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:

Map Your Office's Needs: Define what functions the bot needs to have: answer questions, send documents, schedule appointments.
Create FAQs and Flows: List frequently asked questions and response paths. In Agents with OpenAI Course you learn how to model these flows.
Configure Dify: In the dashboard, create your bot based on the questions and answers, adjusting the behavior.
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.
Automate Repetitive Tasks: Use N8N to trigger automatic responses, save data, and send alerts.
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

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