Algolux, founded in 2015, isn’t exactly a household name in the already crowded world of automotive computer vision. But the Quebec-based startup has generated some interest among investors. For example, it raised $ 13.4 million, including a $ 10 million Series A led by General Motors Ventures last May. Not bad, given that he is still a virtual unknown until now.
Today, Algolux introduces Ion, a platform that gives businesses a set of tools and an integrated software stack to help them. They build their own perception systems. It is essentially a plug-and-play solution, a departure from the common approach today where companies limit themselves to siled systems that often don’t integrate as easily with other systems.
Algolux’s system brings the company’s computer vision and computer learning technologies closer to users seeking to build an end-to-end solution, incorporating various governing body regulations and security features designed to help systems operating in harsh environments.
The company says Ion can be used to make more traditional systems, or “radical new designs.” This capability is applicable to any type of sensor, type of processor and perception task. Ion is based on the Eos and Atlas deep neural network, a number of different modules designed for camera optimization. It provides developers with a mixed approach based on their individual needs.
In a letter to TechCrunch, Vice President Dave Tokic notes that the key differentiator between the company and its competition is a type of brand agnosticism that allows companies to use different products for different needs while keeping costs low.
“Our Ion platform consists of tools (Atlas) and built-in software stacks (Eos) to provide a comprehensive approach to teams building perception systems,” he tells TechCrunch. “This allows the team to optimize and deeply learn both sensing and perception (even down to planning and control) for significantly better performance and to break down today’s design process silos. This capability is applicable to any type of sensor, type of processor and perception task. “