Hyperscience
Bridging the Gap Between Human Understanding and Machine Processing

Automation without accuracy is useless, and high levels of automation alone don’t mean that business processes will run at the quality levels that companies desires or customers demand. To date, organizations have been forced into a trade-off, choosing high levels of accuracy but unreliable results requiring manual review or rekeying, or low levels of automation to ensure accurate results. What they need is an easy-to-use solution that provides real value, including fewer errors and faster processing times, and is designed to scale across an organization and grow with their changing business needs. That’s where Hyperscience comes in.

Since its inception in 2014, the company has focused on sharpening the edges of its Intelligent Document Processing (IDP) offering, which it refers to as “step zero” of its platform. The platform uses cutting-edge AI and machine learning techniques that have been developed and trained for over five years to ingest, classify, separate, and deduplicate diverse documents, including handwritten forms, PDFs, low-resolution images, and more, before extracting and structuring the data for further processing downstream. Customers can set the levels of accuracy they want to achieve, and the solution automates as much as it can and continues to learn and get better over time.

“Our solution knows when it will not be able to deliver expected accuracy levels, and our customers can adjust settings to fit their business conditions and needs,” says Peter Brodsky, the CEO and Co-Founder of Hyperscience. Its built-in quality assurance mechanism helps the machine establish truth in the accuracy of its extraction. This not only provides visibility into the machine and human performance but drives better confidence scoring that helps fine-tune the underlying models. In addition, clients can use its intuitive UI and built-in reporting metrics to drive performance improvements.

“With our dashboard, different stakeholders can see what the error rates are, automation, accuracy, etc. vs. legacy approaches where you don’t have the visibility into on-going operational performance,” mentions Brodsky.

Changing market dynamics and economic uncertainty require an alternative solution to legacy solutions or existing automation tools that only imitate current processes. The company has imagined a future where enterprises build, run and manage business processes like software, and data flows freely within and between organizations. “Being able to understand the data has enabled us to deliver a broad spectrum input-to-outcome automation solution for many business processes. We’re calling it Software-Defined Management,” says Brodsky.

In a software-defined world, decisions are made fast, based on the most accurate data and the most suitable and knowledgeable resource.

Today, Hyperscience is experiencing rapid growth and continues to serve the Global 2000s and government organizations around the world such as TD Ameritrade and many other prestigious companies. In the case of TD Ameritrade, Hyperscience provides them with the ability to automate without sacrificing accuracy, which was paramount for an organization that deals with sensitive customer data where every digit needs to be correct. Further, TD Ameritrade has been able to see value from Hyperscience quickly, and the machine learns and gets better over time. In another instance, Hyperscience has helped a top financial services company to collect twice as much data as a year ago and unlock automation in business groups that has resulted in significant savings in manual effort and time available to focus on more complex work.

With an economic downturn already bringing about an increased level of enterprise automation, Hyperscience aims to use its Series C financing (announced June 2020) to accelerate investment in product development and GTM to bring the next version of the Hyperscience Platform to market at the end of 2020. The input-to-outcome automation platform is fully-customizable with the blocks, out-of-the-box workflows, connectors, and intelligence needed to build, run, and manage most business processes with ease and speed. In the future, enterprises will remove unnecessary management overhead, streamline manual processes and increase the quality of their business decisions, leading to performance-driven organizations with superior outcomes. “For the foreseeable future, humans will remain part of the process. That is why every automation created by the Hyperscience platform has a human-in-the-loop component built-in,” concludes Brodsky.