HyperAspect

The Cognitive Cloud platform

Analysts and decision makers who must act on large volumes of scattered information are the audience for HyperAspect. The flagship is the HyperAspect Cognitive Cloud, a system that pulls data from a firm's own records and from open sources, processes it and presents the results so that people can choose between options with their likely outcomes in view. Its stated aim is to make AI available to organizations beyond a small group of specialists.

Gathering unstructured information

The platform includes data acquisition and extraction tools that gather unstructured material from the web, from social media and from email. The company says this suite can take in large volumes of disparate information from many sources, and that it can be used to build a picture of a market or a set of customers before a decision is taken.

Connecting systems and building logic into data flows

HyperAspect says it links applications regardless of the message format or protocol they use, so that data can move between systems that were never designed to meet. Conditional logic can be built into those flows, and data can be streamed or sent to other destinations with a few steps. The aim is to remove the manual work that sits between one system and the next.

Machine learning and low-code application building

The platform combines deterministic rules with machine learning algorithms. A client can use existing models or build new ones in a low-code environment, and the company says it can help configure machine-learning simulations that find useful patterns and create new analytics algorithms. Applications and dashboards are built on the same base, with data visualization tools and access to prebuilt databases or the client's own sources.

Sector use cases

Applications are arranged under five headings on the site: finance, healthcare, legal, marketing and retail. In healthcare, one use case tracks the condition of patients after treatment in hospitals, to monitor how well a treatment is working and to make overstretched clinical staff more productive. In finance, the platform is described as processing funding requests for venture capital clients, improving vetting, fraud detection, email handling and data checks. A labor-related use case tracks changes inside collective labor contracts to support tax compliance and reduce risk.

Other applications cover supply network optimization, anti-money laundering, customer engagement, credentialing and fraud detection, and price transparency data. The company says its technology stack supports prebuilt, configurable AI solutions for these industries, so that a business can start from a working model rather than from nothing.