How I Created Keppli Finance: An AI-Driven App That Transforms Personal Money - 28/06/2025

Keppli Finance was created to address the financial illiteracy I experienced personally and saw in those close to me. Built with Flutter and NestJS, this AI-powered app acts as a personal financial advisor, making money management easier and helping users improve their financial habits.

Introduction

The lack of financial education has been a constant obstacle in my close circle. Growing up without a strong guide for managing money, I witnessed firsthand the consequences of not understanding basic personal finance concepts. It’s not just a personal observation: a recent report found 38% of surveyed individuals said their lack of financial literacy cost them at least $500 USD in 2022. 15% said it set them back $10,000 or more. Determined to change this reality, I channeled my software development experience into creating Keppli Finance, a mobile application designed to give users the tools and knowledge that so many of us have lacked. Incorporating artificial intelligence (AI) into the project emerged as a natural response to this challenge: why not leverage cutting-edge technology to help others (and myself) take control of our finances in an intelligent, secure way? That’s how Keppli Finance was born. It was conceived not just as an expense tracker, but as a personal financial advisor in your pocket, aimed at helping anyone improve their financial well-being in a transparent and user-friendly manner.

Technical Architecture

From the outset, I knew I needed a solid and scalable architecture. I chose Flutter for the frontend because of its multi-platform capability: with a single Dart codebase, I can deliver a native experience on both Android and iOS, speeding up development without sacrificing UI quality. Flutter excels in performance and has a growing community, and its “write once, run everywhere” promise fit perfectly with the need to iterate quickly on a mobile product. For the backend, I selected NestJS, leveraging my background in JavaScript/TypeScript and modern backend frameworks. Built on Node.js, NestJS provides a modular, robust structure to the project: its design pattern of controllers, modules, and providers made it possible to keep the code organized and maintainable as the application grew.

This combination of Flutter and NestJS allowed me to work with strongly-typed languages on both ends (Dart on the client, TypeScript on the server), and even to share some logic and data models between the frontend and backend, reducing errors and duplicated effort. In terms of infrastructure, the architecture follows a clear separation of concerns: Flutter handles the presentation and user interaction, while NestJS exposes a secure, efficient REST API that orchestrates business rules, data management, and integration with external services. Thanks to these technology choices, Keppli Finance enjoys a frontend that is both visually appealing and responsive, combined with a backend that is scalable and maintainable – a strong foundation upon which to build the app’s intelligent, AI-driven features.

AI-Powered Features

One of the pillars that differentiates Keppli Finance is the integration of AI-based features to simplify and empower the user’s financial management. From the start, I identified key areas where artificial intelligence could add value:

Automatic Expense Categorization

When logging a new expense, the app uses natural language processing to interpret the transaction’s description and amount, automatically assigning it an appropriate category (for example, “Food”, “Transportation”, or “Entertainment”). This automated classification removes the burden of manually tagging each transaction and it learns from the data over time to improve accuracy. In practice, this means if you note “Uber $20”, the app understands it as a transport expense and categorizes it accordingly. Behind the scenes, a machine learning model trained on common transaction descriptions and categories analyzes the text and other parameters of the entry. Based on linguistic and numerical patterns, the algorithm predicts the most likely category for each new expense. Thanks to this feature, Keppli Finance can give users a clear picture of where their money is going without requiring them to have advanced financial knowledge. Intelligent automation of categorization saves time and reduces human error; in fact, today’s AI algorithms are capable of categorizing transactions quickly and efficiently while minimizing errors a capability we have fully leveraged in the app.

Personalized Insights Generation

Recording expenses and setting budgets is only the beginning. The real added value of Keppli Finance comes from its AI-powered financial advisor, which analyzes a user’s financial habits to offer personalized tips and insights. Each week, the NestJS backend compiles the user’s spending, income, and savings data and feeds it into an AI engine that applies pattern recognition algorithms. For example, the AI might detect that your dining-out expenses increased by 20% this month compared to last, or that you are nearing (or exceeding) your leisure budget. Based on findings like these, the system generates natural-language recommendations that are easy to understand. These insights range from savings suggestions (“You spent more on takeout this month than usual; cooking at home a bit more could save you money”) to proactive alerts (“You’re 80% to your savings goal – keep it up!”). The goal is for the user to receive actionable information tailored to their situation – in essence, having a virtual financial coach. User feedback has been very positive: many feel that “it’s like having a financial expert giving clear recommendations” on how to optimize spending and improve savings Technically, this feature was achieved by integrating third-party AI models specialized in financial analysis and language generation, combined with our own business rules. The insights are delivered securely and privately, via in-app notifications and weekly summary emails.

Future Vision: Conversational Voice Interface

Looking ahead, one of the most exciting features on the Keppli Finance roadmap is the addition of a conversational voice interface. The idea is that users will be able to interact with their virtual financial advisor through voice commands or even natural dialogue – similar to assistants like Siri or Alexa, but focused on personal finance. Imagine being able to ask the app, “How much did I spend this week?” or give it instructions like “Log a $50 grocery expense”, and receive an immediate spoken response. This conversational approach, powered by AI, aims to remove usage barriers and make managing finances as easy as having a conversation. To achieve this, I plan to integrate voice recognition technologies and advanced natural language models that can interpret user intent and generate coherent responses. In fact, the current interface already hints at this direction – for example, an “Add expense with voice” button exists in an experimental form, backed by AI to understand spoken commands. The vision is that in upcoming iterations, Keppli Finance will evolve into a true voice-based financial assistant capable of maintaining a dialogue: explaining trends in your finances, answering questions (“How much did I save last month?”), and even giving encouragement or reminders (“Remember, you have a subscription payment due next week”). This future feature builds upon the rapid advances in conversational AIs; we are laying the groundwork to integrate it seamlessly once the technology is ready to deliver an optimal experience.

Agnostic Architecture

To support all these AI functionalities and integrations, it was essential to design a flexible and automated architecture. For this, I used an agnostic architecture approach, which allowed me to orchestrate the application and its automated flows efficiently.

This approach is based on principles and tools applied in Keppli Finance to make the platform as independent as possible from specific technology providers and AI models. In practice, this means we can connect to different AI services and external APIs without relying exclusively on any single one. This way, we can swap or add new models as needed without affecting the stability of the main system. For example, if tomorrow a more precise expense analysis service appears, the architecture will allow us to incorporate it with minimal changes.

Another key aspect was the automation of internal processes. Keppli Finance runs several background tasks automatically: from sending personalized weekly financial reports by email, to performing cloud backups and updating expense categories in real time. Many of these tasks are defined in an automation layer that significantly reduces operational load and minimizes human errors.

To implement this, I used NestJS modules and queues along with cloud services under the serverless paradigm, ensuring functions only run when truly needed. Regarding external integrations, we connect multiple AI models from different providers for features like categorization, insights generation, voice recognition, statistics, and other upcoming functionalities. The coordination between these models is transparent to the user. Thus, if any service fails or delays, the agnostic architecture allows switching to an alternative AI model or retrying the task, guaranteeing the end-user experience is not affected.

We also integrated complementary services like Resend for sending transactional emails and summary reports. Thanks to Resend’s API, Keppli Finance can reliably send weekly reports without needing to build an email infrastructure from scratch.

Next Steps

Developing Keppli Finance has been an exciting journey that combines a personal motivation with cutting-edge technical challenges. In hindsight, the lack of financial education that was once a disadvantage became the driving force to create a solution that now helps others make better financial decisions. Along the way, it reinforced my belief in the power of technology—especially AI—to democratize financial education and improve people’s daily lives. Every technology choice, was made with the goal of building a solid foundation upon which to keep innovating.

Looking ahead, Keppli Finance isn’t stopping here. I will continue iterating and learning from user feedback, refining the app experience and adding new features. The vision of a fully conversational voice interface, for example, comes closer to reality each day as conversational AI technologies mature. I also plan to integrate more data sources and to offer even smarter, more personalized insights as the platform grows.

I invite everyone reading this article to learn more about the project and follow its evolution. Maintaining a professional, transparent, and user-centered approach has been essential to the success of this initiative, and I will continue to uphold these values as Keppli Finance moves forward. While the journey of a developer building their own product as a side project comes with challenges, it also brings great satisfaction in seeing real-world problems solved through code. Keppli Finance is a reflection of my passion for creating useful solutions, and I’m excited for what’s to come. Thank you for joining me on this technological and personal journey, and I encourage you to stay tuned for the upcoming updates from Keppli Finance!