CODEX® Software

The Spatial Biology Company® offers the most comprehensive, end-to-end solutions for high-parameter tissue analysis from discovery through clinical and translational research, which enables the development of more precise therapies for immuno-oncology and other drug development applications.


Spatial Biology

Team size

7 members


2+ years



Business Need

The CODEX (CO-Detection by indEXing) is a technology of Akoya Biosciences that provides a comprehensive solution for spatially-resolved, highly multiplexed biomarker analysis (tissue assay). The technology is powered by complex software products that include a multiplex analysis viewer (MAV), analysis manager (CAM), hardware controlling software – instrument Manager (CIM), and a few other software parts. To be delivered to the actual clients this product required the full implementation of key features. Akoya contracted Akvelon to help the internal development team to deliver the entire solution on time.


The Akvelon team evolved the Swing-based desktop app (MAV) from prototyping to a fully-functioning software with rich data analysis functionality. During the development optimizations of initial algorithms provided several times speedups of application features.

Our team also took part in the development of CAM, a client-server application based on Spring Boot with Angular frontend. The team successfully solved a range of issues related to experiment processing functionality managed via RabbitMQ with MongoDB as storage.

The quality assurance team was involved in comprehensive testing of the software: regression, integration, stress, and system testing.

Benefits and Results

Akvelon implemented all planned key features on time and ensured the quality of the resulting product.

Client benefits:

  • Production-ready desktop app for the experiment results assay was developed.
  • Team’s expertise in technology helped the client to make the solution more stable, reliable, and maintainable.
  • Customers gave positive feedback on MAV improvements during the development.
  • The solution was successfully delivered to the customers’ user acceptance testing on time.

Technology Used

Java, Spring Boot, MongoDB, RabbitMQ, Node.js, Angular, Swing

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