![]() Today, our machine-centric competitors fall into two categories: Companies that provide retrofit automation, layering automation on top of business processes they take from existing technologies, and companies that try to deal with human content using legacy technologies like OCR and speech recognition, to get out of the human layer and immediately back into the machine layer. Underpinning the platform is proprietary machine learning, built-in human-in-the-loop, and graph technology. Customers benefit from a single platform consisting of configurable blocks and flows to process, understand, and take action on unstructured data. Hyperscience creates a truly unique platform in the marketplace. Eight years later, this has evolved into what we now call Human-Centered Automation. Software can do part of the work, but much of it will still need people. ![]() ![]() Hyperscience developed the human-in-the-loop approach rapidly becoming a core tenant for today’s automation solutions. The second insight was that people and software needed to work alongside one another. Hyperscience’s first step was to automate as much of the manual data entry processes as possible. Data was stuck in formats that were easily readable by a person but not readable by machines. But that was not the reality for big enterprises. At the time, everyone was talking about the “data deluge” and how better data meant better decisions. The first was that data entry is a messy and overlooked step. There were two key insights that drove the early creation of Hyperscience and remain key to the way we build products today. Our founding team, including our CEO and cofounder Peter Brodsky, were all software engineers looking to apply cutting-edge machine learning and artificial intelligence to the enterprise. Our industry-leading machine learning technology continuously learns and evolves, to involve humans only when needed. By combining data, people, and processes into digital assembly lines, the Hyperscience Platform turns complex processes into simple, configurable workflows. Our human-centered approach to automation enables a new era of human and machine collaboration that delivers dramatically improved organizational agility, without the legacy cost and burden of change management. Hyperscience is transforming the future of work to elevate human potential. Tell us about the product or service that Hyperscience offers. Investors include Global Founders Capital, Tiger, Stripes, and Bessemer Venture Partners. $100M Series E. Who were your investors and how much did you raise? Hyperscience ensures that users are able to access machine-readable data throughout the organization to more effectively leverage their resources, adapt to changing circumstances, and accelerate digital transformation in a structured, unprecedented manner to have critical information at their fingertips.ĪlleyWatch caught up with Hyperscience COO Charlie Newark-French to learn more about the company’s impressive traction, strategic growth plans including acquisitions, latest round of funding, which brings the total funding raised to $288.9M, and much, much more… By focusing both on the machine layer and human layer, the platform is able to not only introduce the efficiency of technology but also allow the technology to become more intelligent with human intervention guiding the machine learning, creating more time and capabilities both for humans and the tech. Hyperscienceis an intelligent automation platform for document processing that’s centered around a human approach. Businesses must devise solutions to streamline the collection, retention, and use of data so that it’s secure, efficient, and cost-effective. 99.5% of collected data never gets used or analyzed partly because the volume of unstructured data is increasing 35% year-over-year, leaving this data, much of it valuable, in a void. Over the next five years, the amount of data created globally is expected to exceed 180 zettabytes.
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