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Uipath raising there valuation up to $7 billion


Robotics process platform UIPath has targetted IT businesses and raising more than $400 million at a valuation up to $7 billion, sources have confirmed to TechCrunch following a report from Business Insider. Founded in 2005, Uipath till date has raised $409 million and in this new round, there will be an almost second capital increase.

Six months ago, through series C funding of $225 million the business was valued at $3 billion as reported by Pitchbook. Uipath is backed by top-tier investors like CapitalG and Sequoia capital. The latest funding round has been led by a public institutional investor. Generally, Uipath develops automated software workflows to help tasks within the business operation. With this capital increase, it will become the world’s most valued startup surpassing Chinese startup Sense Time.

Uipath termed themselves as Robotic Process Automation company. The company has had particular success with customers in government, from the Army to the IRS. Its software can also be used in banking, running checks on suspicious activity to help a human fraud-prevention analyst.UiPath is part of a new wave of AI software firms with spiking valuations, as venture capitalists jump on the trend of companies trying to automate the most repetitive software processes.

A spokesperson from the company didn’t confirm about the rounds but stated that it would be informed in case of any development although she has also said that the company is facing tremendous growth in recent years and attracting interests from several capitalists. The platform’s core selling point is that it brings automation to enterprise processes. It builds what it calls “intelligent software robots” that help businesses carry out what are often laborious and repetitive tasks using computer vision and rule-based processes. The technology sits atop business applications such as enterprise resource planning (ERP) software and customer relationship management (CRM) tools to emulate tasks usually carried out by a person manually pressing buttons at their desk. These “robots” are trained to observe the interface to see and understand what is happening and then carry out the task as a human would. As with all machine learning applications today, the ultimate promise here is that it will improve accuracy and productivity, allowing human employees to focus on other areas of work. Or, as a more cynical person might conclude, put humans out of work.

This capital investment is a turning point for the company, and surely it will use the resources completely.

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