Python advantages
Ready-to-use open-source solutions
Python enables rapid MVP development thanks to a wide range of open-source libraries.
Easy to maintain and scale applications
With its simple syntax and numerous testing libraries, applications built in Python are more cost-effective to maintain and further develop.
Facilitates the use of business data
Python is an excellent and widely used solution for building solutions in Data Science, Machine Learning, and AI.
Python advantages
Ready-to-use solutions
Multiple open-source libraries that speed up development
Python is widely used for building MVPs due to the abundance of complete open-source solutions that reduce both development time and costs. Tools like Django, Flask, and FastAPI enable developers to quickly and easily create backend systems for web and mobile applications.
This allows companies not only to deploy functional MVPs rapidly but also to ensure easy scalability as their needs grow. For instance, Django is an excellent choice for building e-commerce platforms that initially handle a small number of transactions but are designed to scale effortlessly to manage thousands of users and orders simultaneously.
The availability of these tools lowers the barrier to building your own application, allowing companies to test business ideas more quickly and adapt to changing market conditions.
Easy to maintain and scale
Great for start-ups and scale-ups
With its simple syntax and a wide range of tools, Python applications are easier and more cost-effective to maintain and expand. Python allows for quick and easy implementation of changes, which is crucial for rapidly growing e-commerce or FinTech solutions.
Additionally, Python delivers high performance in managing and processing large datasets, enabling better optimization of business processes through automation.
Facilitates using your data
Leverage your business data for faster growth
Python is an excellent and widely adopted solution in Data Science, Machine Learning, and AI. Teams worldwide are increasingly using this language to analyze data and make strategic decisions based on their insights.
Python offers ready-made solutions that you can use to start leveraging data for decision-making. Practical applications of Python, such as analyzing purchasing trends, personalizing offers, or assessing the profitability of large product portfolios, allow companies not only to boost profits but also to enhance customer satisfaction.
Technologies commonly used with Python
Pandas
A data analysis library that provides data structures and functions for performing operations on datasets. A key tool in Data Science and Machine Learning.
NumPy
The core library for computations in Python, supporting large, multi-dimensional arrays and matrices.
TensorFlow
Advanced frameworks for Machine Learning and Deep Learning that allow for fast and efficient building and training of ML and AI models.
pytest
An advanced testing framework that simplifies writing scalable unit and functional tests.
Flask and Django
Flask is ideal for smaller projects, while Django offers more built-in features and is better suited for complex applications.
AWS
An integrated environment for applications that allows leveraging scalable cloud computing services for rapid development and deployment.
Companies we have worked with
Frequently asked questions
How long does it take to develop an app?
The time required to develop an application largely depends on the features you wish to include. To deliver business value quickly, our aim is to solve your most pressing business challenges within three months of starting our work. We usually observe noticeable results in the first month of work - right after we release the first version of the application to your users.
What if my concept and plan changes during the project?
We know that in IT projects, the scope and needs can change from week to week - which is why our cooperation process is designed to accommodate to frequent shifts. We work in Time & Materials model and rely on Agile Management methodologies. Even if there is a need to change most of the scope, we have no problem with that.
How involved should I be in the software development process?
Many companies hesitate to start building their own solutions due to the complexity of the process and the significant level of involvement required. It often turns out that collaborating on app development requires assigning an internal specialist in the role of Product Owner for a considerable amount of time, which isn’t always possible. Our development process allows us to create effective solutions while requiring only your industry expertise and minimal time commitment to address the most urgent business cases. We will guide you through these processes to deliver the results.
How much does it cost to develop an application in Python?
The cost of a project largely depends on its complexity and the time required to complete it. During our initial meeting, we will provide you with an estimated cost, which typically ranges from €10,000 to several hundred thousand euros. Before we begin, we analyze your specific business case to determine whether working with us will be profitable for you within a realistic timeframe. If we believe that proceeding with the project may not be cost-effective, we will inform you directly.
Can you take over a project from another company?
Yes. A significant majority of our clients have previously worked with other development companies that did not deliver the project or where communication between their teams was not perfect. Contact us to share your situation-we will prepare a recovery plan to save your time and budget.
Contact
What can we do for you?
Ask us anything - we are eager to learn more about your needs and show you how we can help.
The first step is scheduling an online meeting where we will get to know your business better and gather information about the issues you aim to solve.
We will also answer any questions you have about the project and our previous work.