Redactable is an AI-driven web application that is designed for redacting sensitive documents of its clients. Recently, it has successfully secured a hefty amount of $5.5 million in its seed funding round which made a significant financial boost to the profit of the company. It was actively led by participation of companies like Gradient Ventures, Google’s AI-focused venture fund, with contributions from Wocstar Fund, earlier pre-seed investors, and several influential angel investors.
The company’s innovative AI-driven platform has a unique function in detecting and effectively working on permanently redacting sensitive information in documents that tends to offer more reliable options to the companies.
This round of funding arrives over a year after Redactable’s initial $1.3m pre-seed funding which was supported and funded by investors like Everywhere Ventures, Hustle Fund, Revelry, and Stony Lonesome Group. These investments kick-started the platform’s launch in July 2022.
In today’s digital age, where sensitive data sharing is getting a common practice, Redactable’s solution is increasingly relevant to the matter’s safety for both firm and the customer. Traditional PDF editing tools and legacy software often fail to fully conceal confidential data, posing a risk of exposure. Redactable’s platform addresses this challenge by providing a secure and efficient redaction process to its clients.
The significance of Redactable’s technology is underscored by its recent $1.25m U.S. Air Force contract passed out. The following contract will utilise the company’s patented software to shield sensitive documents and streamline business processes within the Department of the Air Force (DAF) successfully.
Amanda Levay, Redactable’s founder and CEO, shares her concern and opinion by highlighting the growing need for secure data sharing. She states that, “With so much confidential information being shared electronically, the risk of data vulnerability for both individuals and organizations is increasing exponentially. Too much time is spent using black markers or drawing boxes over sensitive data, which is not only inefficient but also ineffective.”
