A couple of pieces of funding news in the artificial intelligence space; AI-powered service provider Logz.io has secured $23 million in series C funding, while imaging analytics company Arterys closed a $30 million series B round.
Logz.io is an intelligent log analytics platform that synthesises machine data, user behaviour, and community knowledge to provide timely actionable insights to operations. It uses the combined power of machine learning and open-source ELK (Elasticsearch, Logstash, Kibana) stack.
Two new features are introduced in the platform to empower customers to attain the most value from their data: Application Insights and Data Optimizer. Application Insights enables faster incident detection and resolution of critical application issues. Data Optimizer empowers enterprises to reduce the cost of data retention by determining which logs have value and how long they should be stored.
Logz.io’s funding was led by OpenView with participation from investors 83North, Giza and Vintage Investment Partners. The company, whose customer base has more than more than tripled year on year to reach more than 400, will utilise the new funding to fuel new product innovations and expand its current headquarters in Boston, MA.
Arterys, an imaging analytics company fusing AI and cloud computing, had its funding round led by Temasek, along with Varian, Northwell Health Ventures, NewYork-Presbyterian, GE Ventures and several leading venture investors. The funding will be directed towards expanding its web-based artificial intelligence platform, launching new products in oncology and neurology, and to accelerate the commercialisation of its cardiac offering.
Fabien Beckers, founder and CEO of Arterys, said: “This financing includes pioneers in healthcare who recognise the game-changing value of a cloud AI platform to unlock the potential of radiology data to improve patient care. We are excited to grow our offerings and work with our clinical partners in building powerful, accessible tools for the medical imaging community to accelerate the transition to data driven medicine.”
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