Neodev Studio

With Neodev Studio we offer full in-house development from our offices in Malmö. In close collaboration with our customers we handle projects from start to finish.

Some of our clients.

2013

Neodev is founded by a couple of old colleagues. Their vision is an employee-owned company with focus on “the boundary between development and testing”. The values are openness, honesty, compassion and enagagement.

2014

Neodev is awarded 100 KSEK from Almi in order to develop a testing framework (known as “Vizte”) to offer clients as a way of kickstarting their test automation.

2017

The company decides to focus on software engineering instead of just test automation.

2018

Neodev bets on machine learning and starts a series of seminaries and workshops related to the topic. Our first course “Introduction to Machine Learning and ANN” is held in December.

2019

The machine learning course has become a success and is held 8 times in the year. Several of our machine learning experts are out on assignments. Neodev is awarded the “Gasellföretag” title from Dagens Industri.

2020

We move to our own offices on Södergatan 3 in Malmö, which opens up for full in-house projects. Neodev wins a hackathon arranged by Helsingborg city.

2021

With several successful projects in the bag, Neodev Studio projects now account for about 25% of our revenue!

Neodev Studio

Digitalization & the Cloud.

A typical Studio project often revolves around taking a pre-existing, often archaic, application and moving it into the present. We re-imagine old Pascal applications as user friendly web applications and build them on top of the latest cloud technologies.

The gains are enormous and usually lead to kick-starting broader digitalization efforts where old services start to become interconnected and new exciting possibilities open up!

  • studio@neodev.se
  • +46 (0)73 385 69 15

Previous projects.

Web application

Automotive

Web application for online, real-time, production line visualization.

The application shows information about produced components as well as the status of the different production lines and the components in production. The project included the development of a design language, component library and UX design as well as a Node.js backend (FoalTS, TypeScript) that acts as a middleware for the existing MS-SQL databases. The front end is mobile friendly and presents the production data in a user friendly manner, developed in React (TypeScript).

[Node.js, JavaScript, TypeScript, React, FoalTS, MS-SQL]

Systems development

Machine learning

Developing a machine learning framework for use in a real estate system with a React-based front end hosted on GCP. The framework includes data upload, model training, evaluation and prediction.

[NLP, FastText, Python, Node, scikit-learn, GCP, Firestore, Cloud run, OpenAPI, JWT]

App development

Machine Learning

Hojta!

We participated in a hackathon (Inhabitation) arranged by Helsingborg city. The challenge was to solve the digital exclusaion of elders (70+ years) in society. We created an application with a Tinder-like UI where people could match up based on common interests. As winners of the hackathon we received prize money to continue the development and present a fully working prototype.

[React, JavaScript, Google Cloud, git, CSS]

Systems development

Machine learning

Vinnova project - Integrating a new AI-module into an existing system. The module was used for categorizing textual data in different classification systems, including text pre-processing and implementation of models for embedding words.

Front end development for this system, including a user interface in React to ease the data gathering and demonstrate the categorization. [NLP, Python, React, MongoDB, React, Javascript, Flask]

This client also let us modernize their existing web application from jQuery and webforms to React.

[Git, React, Javascript, C#, ASP.NET, .NET framework]

App development

Machine learning

Design and development of a mobile first ‘sample gathering’ web application with a server-less backend in Azure. Implementation of model training and versioning pipeline. The models where used by another web application for prediction through a real-time Tensorflow JS implementation.

[Python, Node, Tensorflow, Keras, Javascript, Azure (Cosmos DB, Functions)]