Bioprocess industry
data scientists data
analytics tool

Bioprocess Industry
The Freesense App is a data analysis tool to process data collected from patented sensors that provide data-based tank mapping service for the Bioprocess industry. Developing a web application that helps to analyze & visualize the data from sensors was a critical factor in creating a competitive advantage in their product.


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What we do

Our Role

We were responsible for converting the client's business requirements and scaling the idea into a well-designed tool which covers data-scientists needs.

This solution processes large data sets from sensors (.csv format) into various data visualizations and analysis models. Thanks to accurate output, a data scientist can optimize the fermentation process in their industries

What client do


Freesense is a Danish sensor-tech company and data provider for the global bioprocessing industry. They have developed wireless sensors and data analysis platforms for monitoring fermentation processes where data is either not detailed or non-existing today. Their patented sensor technology, together with novel data analysis methods, is used in various liquid bioprocessing applications around the world, enabling the user to gain a better understanding of what is going on inside fermentation tanks. Freesense's technology Users in the fermentation industry are continually looking for tools to enhance their processes in stirred bioreactors. Freesense offers a data-based mapping service based on their patented FermSense 3D sensor technology. FermSense 3D is a sensor explicitly designed for the rough environment in an agitated bioreactor. The device is able to collect data like pH, temperature, pressure, position, flow throughout the process.

How does it work?

Step 1


The client buys the service and deploys the Fermsense 3D sensor in the tank. 45 mm

Step 2


The sensor floats in the tank for a certain amount of time, collecting data like pH, temperature, pressure position, flow.

Step 3


The client's data scientists can work on data visualization and analysis collected from highly accurate sensors with data from the entirety of the fermentation vessel unlike the localized data they use today. This enables the scientists to gain a much more in depth understanding of their process and optimize accordingly.

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Delegation of work

Until now, Freesense scientists have created optimisation reports. Now client scientists can do the data analysis & visualisation by themselves and compare their datasets.

Automate the process

Clients will have access to the data immediately after the data collection process ends. The web app stores the data and allows the user to conduct.


Our process

Bioprocess Industry - Our process - Idego


Review the client's materials

Freesense gave us the requirements and existing materials for the project. Based on these, we've created a scope and detailed backlog.

The project was conducted using an Agile Methodology. Every Monday, we were planning work for the upcoming week, ending with a demo session of our outcome.


There are no direct competitors currently on the market as Freesense acquires unique data with its patented sensors. Although, there are multiple data visualization & data analysis tools like Tableau, JMP, which we review with a focus on presenting graphs.

Design Challenge

The main challenge was designing the optimal solution for the deep structure of the processes while keeping high usability and excellent user experience.
Each project has its database of uploaded files. Projects contain runs and comparisons modes. Each of them has each separate dataset. Each run and comparison provides one of five visualization methods.


Research phase

The client (Chief Operating Officer and Product Owner) visited our office in Gdansk, Poland,

The topics we worked on:

  • project management and future cooperation
  • the business model of the company
  • a plan for the expansion
  • the needs of the users
  • reviewing the existing wireframes
The workshop is also an occasion to build a relationship with the client. The better communication is between the sides, the more obstacles we can avoid in the next phases of the project.

Who will use the app?

The users of the app will be highly qualified Ph.D. scientists, 30 years old+, located around the world, working in labs in the bioprocessing industry. Their goal is to optimize the process by using data.

Who will buy the app?

Freesense clients are bioprocessing companies.



Reevaluating a goal
The client's goal was to design the flow so that the user could see data visualization as quickly as possible. While working on the solution, we realized how many steps a user needs to take before actual data visualization occurs (including file transfer, tank configuration, timestamp). We came to the conclusion that a given goal does not provide a good user experience. Navigation in the application should be more user-friendly and cause less confusion for the user. The lesson we took was to re-evaluate the client's goals, focus on the user experience, and re-design our approach.

Choosing data processing method
A user can select one of five data processing methods. It is the last step before working with the data. However, users can open multiple processes at the same time to compare different plots or data. xt phases of the project.

Bioprocess industry - Wireframing - option-1 - Idego Option #1
Bioprocess industry - Wireframing - option-2 - Idego Option #2

User Testing

We did the remote user testing on wireframes with data scientists from Denmark. We had a fantastic opportunity to see how end-users interact with our designs. Talking with data scientists and asking them what is missing or what we could improve was an invaluable experience. Based on those testings, we made a few improvements.

Expanding the scope
During the interacting with users, they suggested the addition of new features, new functionalities and new data processing methods. We need to be careful to fulfil the user's needs but keeping in mind the business side of the project, including time and budget. For the Minimal Viable Product (MVP) we cut the scope of features which the app will offer.

Settings - User testing - Idego


Data scientists split data using comma and semicolon as a separator for numbers Having adjustment of units and time-format meets the standard for customers all over the world.

Assingning variables - User testing - Idego

Assigning variables in basic plots

The Data matrix works for choosing what variables from the data files (.csv) users wants to visualize on the plot. The previous method wasn’t clear for our testers. Based on their experience, we created a different way to assign variables to each other.


User Interface Design

Brand attributes

Data scientists are used to working in desktop applications with old-fashioned design (see the moodboard). Our intention was not to provide too colorful, flashy design. Less is more.


The requirement was not to use multiple colours, but to create a clean visual design. We used a Freesense brand palette.

UI Material Design

We consulted a UI approach with our developer. Based on a tight deadline, we decided to use the React Material design library. Thanks to this approach, the development stage was done faster and cheaper.

Bioprocess industry - User Interface Design - Idego
Bioprocess industry - Wireframe: Basic plot - Idego


For managing multiple files, we decided for a typical “Folder” navigation to give a clear vision of the structure.

Bioprocess industry - Database - Idego
Bioprocess industry - The Panel - Data Files - Auto saving - Plot - Idego

The Panel

One of the main duties of scientists in is the possibility to compare multiple runs inside of one project. A user can open a new, clear tab or load already saved one.

Data Files

A user can upload data files and use it for particular analysis.

Auto Saving

To prevent loss of project progress, we added the ‘auto-saving’ feature instead of saving each file manually.


A plot is generated automatically and changes in real-time. Software engineers chose Plotly as a tool to visualize data. It is built by Python and Django framework.

Bioprocess industry - Last photo - Idego
Client's sketch: Projects list Wireframe: Projects list Final version: Projects list

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