Welcome to the Xano Course: The Power of No-Code Backend! In this course, you will have the opportunity to learn how to take your first steps in the biggest backend in today's Code, Xano. With Xano, you will be able to scale your projects with thousands of users and enjoy the benefits of the tools in Code, offering agility and flexibility.
This practical course offers the opportunity to learn from instructor Louis, a specialist in the Xano Backend tool and one of the biggest names in the area in Brazil. Furthermore, Louis is part of the Xano team in the United States, which makes him one of the biggest market references in relation to Xano.
Before starting the course, it is important to review some fundamental concepts. A software always consists of a front-end and a back-end. O backend is responsible for all aspects of the database, data management, authentication, user security, media storage, server actions and webhooks.
Important Concepts
Fundamental concepts that are essential to fully understand how Xano works include APIs, CRUD actions, and database usage.
APIs
Firstly, we have APIs, which are used for communication between systems. In the context of Xano, they are vital for connecting the front-end and back-end, allowing the exchange of data necessary for the application to function.
CRUD Shares
Continuing, we have the CRUD actions (Create, Read, Update, Delete) that are fundamental for interacting with the database. They allow the creation, reading, updating and deletion of data, providing the necessary functionalities to manipulate the stored information.
The Power of Xano
Xano is a powerful no-code backend that offers agility and flexibility in building applications. Xano's advantages include the use of the Postgres database, which is highly scalable and secure. Furthermore, Xano offers the ability to build APIs easily, allowing the creation of new functions and interactions with the database quickly and flexibly.
In addition, Xano is also compatible with the most important data protection and compliance certifications, such as SOC2, GDPR, IPA and ISO 27001.
Finally, Xano allows the creation of APIs in an easy way, with the ability to create, read, edit and delete data from the database, all through APIs, facilitating integration with other no-code tools. In this way, Xano stands out as a practical, flexible and secure tool for connecting the front-end with the back-end.
Starting the Xano Course
Now that you've realized that Xano is an incredible tool, let's move on to the practical part, and that's why I invite you to watch the video below that contains the complete Xano course.
Conclusion
Now that you know the basics about one of the best nocode backend tools on the market, share your opinion in the comments! And if you have any questions, leave a comment and we will be happy to answer.
And so, for those who want to learn how to use Xano professionally in conjunction with other front-end tools and be able to create an application from scratch, we have several courses and learning paths.
We are living in an era where texts, images and videos can now be created by artificial intelligence. But there is one element that is gaining strength as a competitive advantage: the voice.
Whether in podcasts, institutional videos, tutorials or even automated service, the ability to create realistic artificial voice is changing how companies and creators communicate. And in this scenario, the ElevenLabs AI emerges as one of the global protagonists.
What is ElevenLabs?
O ElevenLabs is one of the neural speech synthesizers most advanced on the market. With its technology AI voice cloning and AI-powered text to speech, allows you to create realistic voices in multiple languages, with natural intonation, dynamic pauses and surprising emotional nuances.
Key Features:
Human-quality Text to Speech
Conversational AI with support for interactive agents
AI-generated voices can be used commercially, as long as you respect the platform's Terms of Use and do not violate third-party rights by cloning real voices without authorization.
Is it possible to use ElevenLabs for free?
Yes. ElevenLabs offers a free plan with 10,000 credits per month, which can be used to generate up to 10 minutes of premium quality audio or 15 minutes of conversation
This plan includes access to features like Text to Speech, Speech to Text, Studio, Automated Dubbing, API, and even Conversational AI with interactive agents.
Ideal for those who want to test the platform before investing in paid plans.
What is the best alternative to ElevenLabs?
Other options include Descript, Murf.ai and Play.ht. However, ElevenLabs has stood out for its natural voice, advanced audio editing features with AI, API integration and support for multiple languages.
Their paid plans start from US$ 5/month (Starter) with 30 thousand monthly credits, and go up to scalable corporate versions with multiple users and millions of credits.
You submit a text, choose a voice (or clone one), and AI converts that text into realistic audio in seconds. It can be used via the web dashboard or via API for automated workflows.
Examples of using ElevenLabs AI in practice
1. Video and podcast narration
Ideal for creators who want to save time or avoid the costs of professional voiceovers.
2. Automated service with human voice
Turn cold bots into realistic, empathetic voice assistants.
3. Generating tutorials and training with audio
Companies and CLT professionals can create more engaging internal materials.
4. Applications that “talk” to the user
With tools like Bubble, FlutterFlow or WebWeb, it is possible to integrate AI voice into apps.
How to integrate ElevenLabs with NoCode tools
N8N + ElevenLabs API
Allows you to automate voice generation based on dynamic data using visual workflows in N8N. It is ideal for creating processes such as audio customer service responses, automated voice updates, and more.
With the use of AI agents, it is possible to create voice-responsive systems, such as a virtual attendant that speaks to the customer based on a dynamic prompt.
Use the API to insert audio into your apps with interaction triggers or dynamic events.
ElevenLabs and NoCode: Open the door to creating experiences with voice AI
AI-generated voice is already a powerful, accessible and potential-rich reality. ElevenLabs is not just a tool, but an engine for creating immersive, automated and more human experiences.
If you want to learn how to integrate these possibilities with NoCode and AI tools, NoCode Start Up has the ideal paths:
The market is changing – fast. Artificial intelligence is no longer a trend, it has become a necessity. Companies are cutting costs, optimizing operations and looking for specialists to implement AI in their daily lives. And this is exactly where the AI profession comes in. AI Manager Course.
NoCode AI Manager Course: What it is, Who it is for and What its Objectives are
THE AI Agent Manager Training It is aimed at anyone who wants to enter the field of artificial intelligence in a practical way, without needing to know how to program.
The main objective is to train professionals capable of delivering automation and real solutions for companies using NoCode tools.
It is ideal for both those who want to offer services and those who want to open their own AI agency.
The training proposal is clear: enable you to bill more than R$14,000 per month working with intelligent solutions — a market that is only growing.
The training is structured in complete knowledge trails, with content organized by theme and level of mastery:
Topics covered:
Fundamentals from Zero to Advanced
Mastering Automations with AI
Creating and Selling AI Agents to Companies
Applied Prompt Engineering
Using NoCode tools like n8n, Dify, Make, OpenAI and more
Integration with WhatsApp, CRMs and payment gateways
Ready-to-clone and apply templates
When you sign up, you get:
8 complete formations, including SaaS AI and technical courses from NoCodeStartUp;
Access to exclusive community, active and with direct support from instructors;
1 year full access, including the Make paid plan;
NoCode Match, a hub of real opportunities in the AI and automation market.
Differences between AI Manager Training and Other Courses
Unlike many generic courses, this training was designed as a complete ecosystem of learning and practical application, with total focus on generating results for the student.
100% classes structured, edited and with step-by-step teaching methods
Mentors present, community engaged
Trail with beginning, middle and end, organized with teaching methodology
Real opportunities and networking with companies and devs
Masterclasses with experts who already apply AI in agencies and companies
What is the cost of the AI Manager Course and Access Conditions?
The promotional value of the training is R$ 1,497 in cash or in up to 12 installments of R$ 157.53 on the credit card.
Full access for 12 months
7-day money-back guarantee
Updates included at no additional cost
FAQ: Main Questions About the AI Manager Course
Do you need prior knowledge? No. All content is designed for absolute beginners in AI and NoCode.
How long do I have access? You will have 1 year of access complete to the platform and updates.
Can I ask for a refund if I don't like it? Yes. You have 7 days warranty to test and cancel without bureaucracy.
I'm a PRO student. Do I already have access? Yes. NoCodeStartUp PRO subscribers have unlimited access to the training.
What are the extra costs for tools? The only initial cost for teaching purposes is US$ 5 to use OpenAI API.
How long will it take for me to see results? In the first few days, you can create and test your first AI agent.
What do I get when I purchase? Immediate access to all tracks, bonuses, community, templates, Masterclass and tools.
How to Become an AI Manager?
To become an AI manager, the ideal is to start with training that combines practice and theory in an accessible way.
The NoCodeStartUp course focuses exactly on that, teaching how to create automations with AI without requiring prior programming knowledge.
You'll learn everything from the fundamentals to delivering real solutions using platforms like n8n, Make, Dify, Zapier, and OpenAI.
How Much Does an AI Manager Earn?
According to the market itself and reports from students, an AI manager can earn above R$10 thousand per month, working with consultancies, creating personalized agents or recurring services via intelligent automation.
Which Course Should I Take to Work with AI?
If you are looking for a practical, up-to-date course, with a strong connection to the market and no programming requirements, AI Agent Manager Training is one of the most complete currently.
It combines technical content with real-world application so you can start working quickly.
Invest in Yourself: Become a Professional AI Manager
If you are looking for a way to stand out in the digital market, enter the technology area without having to program and act with something that is growing rapidly, this course is a smart shortcut.
The AI Agent Manager Training provides a clear path, real support and applicable tools for you to work with AI in a professional manner.
It is applied learning with a total focus on solving real problems using artificial intelligence.
Artificial intelligence (AI) is reshaping the way the financial sector operates, from risk analysis to the automation of complex processes. More than a trend, AI has become a strategic tool for financial institutions that want to increase their efficiency, reduce costs and offer personalized experiences. Within this scenario, the use of AI agents for finance has been gaining ground as a practical and accessible application for companies of all sizes.
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.
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 toVisa, 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.
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