Hyperscience unlocks GenAI for mission critical applications with Hypercell
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Hyperscience unlocks GenAI for mission critical applications with Hypercell

CIO Review

Hyperscience, a market leader in hyperautomation and a provider of enterprise AI infrastructure software, is introducing a new solution that brings the back office into the GenAI age, fine-tuning LLMs with ground truth documents embedded at the core of the enterprise.

Hypercell for GenAI automatically annotates, labels, and structures data from documents for fine-tuning LLMs and GenAI experiences, allowing organizations to rapidly and continuously develop highly accurate, relevant, and valuable enterprise models, according to the company.

Through a trusted and proven interface, businesspeople can use Hypercell for GenAI to accelerate mission critical workflows, grounded in secure, proprietary data, and tuned to the business.

Hyperscience is working with Google Cloud, Hewlett Packard Enterprise (HPE), and other partners on this solution, to give customers flexibility to operate in the infrastructure and AI development platform of their choice, to enable use cases such as prompt engineering, RAG, grounding, and vector search on the customers’ proprietary enterprise data, according to the company.

“The success or failure of any AI initiative starts with the data that feeds the models,” said Andrew Joiner, chief executive officer, Hyperscience. “Too often, models are built on faulty and incomplete data, and inefficient manual methods and legacy technologies struggle to keep pace with the dynamic flow of documents that course through organizations every day. Today, Hyperscience provides a breakthrough to this challenge by allowing organizations to establish an accurate data estate that trains LLMs to speak the language of their business, and empowers users with relevant, in-context GenAI experiences that align with their business processes and use cases.”

Hyperscience aims to disrupt the status quo with a novel approach built on AI at its core. Based on a proprietary, machine learning model-based architecture that reads and understands content fluently, Hyperscience delivers industry-leading accuracy rates of 99.5% and automation rates of 98%, as per the company.

Designed with simplicity, business users can train and manage models based on their domain expertise, and the Hyperscience platform's blocks and flows enable process orchestration and integration with downstream enterprise applications.

Hypercell for GenAI leverages the same core technology for hyperautomation, to rapidly transform complex documents into LLM and RAG-ready data, accurately, automatically, and continuously.

Hypercell for GenAI establishes a comprehensive data estate to power relevant, in-context GenAI experiences. The solution provides a simple user interface that delivers trusted, accurate results as part of a business user’s workflow.

Hypercell for GenAI can run on-premises, in a hybrid cloud, in a public cloud, in a SaaS environment, and even highly secure air-gapped environments. Built with the highest security, governance, compliance, and traceability standards, the offering is well suited for use cases in regulated industries and the public sector. Hypercell for GenAI provides a cutting edge architecture that enables organizations to deliver enterprise AI cost effectively, on top of CPUs or GPUs. 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 is collaborating with Google Cloud and Hewlett Packard Enterprise, leveraging AI software that accelerates AI model development by transforming complex documents embedded at the core of the enterprise into an accurate, AI-ready data estate for applications, including generative AI.

Hypercell for GenAI will be available on Google Cloud Marketplace or directly from Hyperscience. Hypercell for GenAI leverages the core capabilities of the Hypercell, an all-in-one AI infrastructure software platform that accelerates enterprise AI initiatives at scale.

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