Ainomaly, a machine learning company for the Automotive industry, makes software safer using AI. They have optimized the product ROBOTest for complex, safety-critical, real-time systems.
Ainomaly is on a mission to make software developers everywhere more efficient and development teams more productive.
The algorithms in Ainomaly’s solution reduce the time to market for bug-free code. In the market for Autonomous Vehicles, this translates directly into safer solutions on the road at a lower cost.
85% of the functionality in modern cars is controlled by software and the speed of software development is already too fast for traditional software quality assurance (SQA).
High profile accidents such as the Uber crash in Arizona demonstrate the importance that autonomous vehicles must meet stringent safety standards. It is no surprise that the cost of taking ADAS Level 3 Automation to market is 80% higher than Level 2, and Level 4 automation is 360% more expensive again. Much of this cost is due to software complexity.
Ainomaly applies eXplainable AI to deliver autonomous software testing seamlessly integrated into existing test automation workflows. Ainomaly takes SQA from brake to turbo.
- Prof. Karl Meinke (KTH-EECS), has over ten years’ experience of research and industry collaboration in applying machine learning algorithms to autonomous, black box testing of software. Karl is a global thought leader in the field of Learning-Based Testing.
- Mr. David Berglund is as seasoned executive with over 20 years management experience in leading and developing high-tech companies across international markets.
The idea comes from more than 10 years of research at the KTH Department of Computer Science. David and Karl met over a cup of coffee in Karl’s kitchen during a play-date.
If you would like to learn more, give them a call on +46 761 19 99 31.