Hyperscience presents a new solution for unlocking GenAI for mission-critical applications: @VMblog

The company Hyperscience has introduced a new solution that brings office processes into the era of artificial intelligence, thanks to the precise tuning of large language models (LLM) using relevant documents that underpin the business. The Hypercell system for GenAI automatically annotates, labels, and structures data from documents, allowing for the rapid and continuous development of highly accurate, relevant, and valuable business models. With a reliable interface, business users can utilize Hypercell for GenAI to accelerate critical workflows based on secure, proprietary data tailored to the specific needs of the business.

Hyperscience actively collaborates with Google Cloud, Hewlett Packard Enterprise (HPE), and other partners to provide clients with flexibility in working with infrastructure and artificial intelligence platforms of their choice, which facilitates the implementation of use cases such as query engineering, RAG, data updating, and vector search based on companies' proprietary data.“The success or failure of any initiative in the field of artificial intelligence starts with the quality of the data used to train the models.”– noted Hyperscience CEO Andrew Joyner.“For too long, models have been built on poor-quality and incomplete data, while outdated technologies and inefficient manual methods have struggled to keep up with the fast flow of documents that organizations receive every day.”Today, Hyperscience offers a solution to this problem by enabling companies to create accurate datasets for training LLMs, making them speak the language of business and providing users with a GenAI experience that aligns with business processes and practical tasks.

In the last ten years, companies have been striving for digital transformation to automate, modernize, and compete in a dynamic, fast-changing market. Traditional methods of Intelligent Document Processing (IDP), Robotic Process Automation (RPA), and Optical Character Recognition (OCR) have failed to meet the expectations of digital transformation, as they are rigid and based on fixed rules, unable to handle new, diverse, and complex documents within the company. These solutions have shown unsatisfactory results in terms of accuracy and required significant manual labor costs from outsourcing companies (BPO) to automate processes and workflows within organizations. Hyperscience has crossed this boundary by offering a new approach based on artificial intelligence. With a unique architecture built on a machine learning model capable of freely reading and understanding content, Hyperscience demonstrates minimal error rates of 99.5% and automation rates of 98%.

Designed with simplification in mind, Hyperscience tools allow business users to train and manage models based on their professional experience, while the blocks and flows of the Hyperscience platform provide orchestration of processes and integration with the company's application solutions. This opens new horizons of productivity for organizations, enabling them to connect processes and solutions from the back office to the front office, making Hyperscience a market leader in the rapidly evolving hyperautomation sector.

Currently, Hyperscience is expanding hyperautomation with GenAI in business. Until recently, LLMs were primarily trained on publicly available data but faced challenges in obtaining and delivering accurate results based on data and documents from the office environment, such as forms, invoices, insurance applications, bills of lading, and more.

Hypercell for GenAI creates a comprehensive dataset that enables the delivery of relevant and contextually meaningful GenAI experiences. The solution offers a simple user interface that ensures reliable and accurate results within the business user's workflow. For example, a claims specialist can use Hypercell for GenAI to inquire about the status of a claim based on a natural language request. The system is capable of transforming complex documentation, such as forms, medical reports, receipts, and doctor's notes, into RAG-ready data for summarization and providing recommendations to users on whether to approve or deny a claim based on current data.

Hypercell for GenAI can be installed in local mode, in a hybrid cloud, in a public cloud, in a SaaS environment, and even in highly secure isolated environments. The system is designed with high standards of security, management, compliance, and traceability in mind. This makes it an ideal solution for use in regulated industries and the public sector. Hypercell for GenAI provides a modern architecture that allows organizations to effectively develop artificial intelligence for business based on processors or graphics processors. The solution supports a wide range of LLMs, including Mistral Large and Mistral 8X22B, Llama3 (including all three versions), and GPT 3.5 and 3.0.

Hyperscience collaborates with Google Cloud and Hewlett Packard Enterprise, using artificial intelligence software that accelerates the development of AI models by transforming complex documents embedded within the company's structure into accurate, AI-ready datasets for various applications, including generative AI.

As part of its global campaign, Hyperscience today unveiled Hypercell for GenAI, featuring billboards in London, Salt Lake City, Sofia, Bulgaria, and Times Square in New York City. Additionally, the company announced significant progress, including record results for the first quarter of 2024, record customer retention rates, and strategic wins among clients.

Hypercell for GenAI will be available on Google Cloud Marketplace or directly from Hyperscience.