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San Jose-Based Firm Functionize Gets USD16 Million In Series A To Automate Software Testing With Artificial Intelligence

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San-Jose-Based-Firm-Functionize_Gets-USD16-Million-In-Series-A-To-Automate-Software-Testing-With-Artificial-Intelligence San Jose-Based Firm Functionize Gets USD16 Million In Series A To Automate Software Testing With Artificial IntelligenceThe developer of a Cloud-based platform that autonomously discovers software bugs, Functionize has achieved a sum of total USD16 million in Series A funding round that will support to automate software testing with Artificial Intelligence-powered solutions. The funding round was led by Silicon Valley-based Canvas Ventures, a group of early-stage capital investors which specializes in FinTech, Health IT, Big Data, Mobile and Enterprise investments. With this capital round, the company’s total valuation has reached to USD 18.2 million, including a USD 2.5 million seed funding round in February last year.

Founded in 2015, Functionize Founder and CEO Taman Cser stated that the developers and analysts still maintain experiments the same approach as they did in the early age of the internet. But, the company’s solution enables them to just work and empowering to drastically accelerate product delivery. Based in San Jose, CA, Functionize’s Software-as-a-Service (SaaS) combines with DevOps platforms such as Jenkins, Bamboo, and AWS Code CodePipeline and leverages NLP (Natural language Processing) that allows developers to tests in simple English, which it transforms into test cases. The tests are configurable to a degree where developers can identify things like region, orientation, and resource type, and they explore various features, ranging from API calls, two-factor authentication, cookie storage, and imperceptible elements.

Functionize, at the conclusion of each test, found out a performance table that is segmented by browser, device, and environment, comprising DNS lookup times, page load speeds, and a proprietary visual performance metric what the company calls ‘visual completion’ that tries to model the timing thresholds of every aspect of the user experience. Further, it creates a geographic overview of insights from all of the company’s existing testing servers, and graphs highlights page speed and previously loaded time by connection type, page, and region.