We build custom enterprise-grade digital products. Our services include product research, design, enterprise software development, application modernization, BA, QA project management and tech consultancy, e.g. Agile methodology consulting, AI use case prioritization, We are also Okta, Camunda, and Digital. ai consulting and integration partners.
Developing software release and deploy automation tools for a Gartner Magic Quadrant leader. Access to expert talent: scarce Scala & Akka skillset
Lack of senior expert leadership for a globally distributed engineering team.
We’re a team of more than 100 people using agile methodologies to create high-quality products for our clients. Because of this, we’re never standing still. We’re constantly seeking and experimenting with different product development best practices to improve the team’s happiness and how we integrate all of our cross-functional skills in Engineering, Design, Support, Operations, and Management.
Winphar - AI Stock ManagementIn 2012 we were challenged to take an outdated pharmacy management software program and renew it, making it more robust and secure, yet flexible and easily adaptable to constantly changing business rules.
Winphar is the second largest operator on the market.
SoftwareMill takes care of the complete project development process, always keeping in mind that we want to develop maintainable, working software that brings real value to our clients.
We build on traditional engineering work ethics and values, which translate directly to the quality of our systems, helping the client discover their true needs.
Our specialization is distributed systems, big data, blockchain, ML, and data analytics. Out technology stack: Scala, Kafka, Akka, Cassandra. We help teams get up to speed with functional programming, introduce event sourcing, or define streaming data pipelines.
ChatGPT
Banking & Trading Platforms
SaaS
Home Automation
AI & ML Solutions
Java
AWS
More +
CASE STUDIES
End-to-End transportation mode recognition softwareReasonfield Lab by SoftwareMill was to create an end-to-end solution for the Codos Foundation, which involved detecting transportation modes based on data from mobile phones. The goal was to calculate CO2 emission avoidance to reward users for sustainable commuting. The project required high precision in machine learning models and handling continuous mobile sensor data. Understanding the spatial context was crucial since user motion occurs in cities, making the task a challenging combination of science and engineering.