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Hercules AI Unveils a Novel ’Assembly Line’ Approach and ’RosettaStoneLLM’ for Generative AI in Regulated Industries


CAMPBELL, CA – WEBWIRE

Today, Hercules AI, initially known as Zero Systems, introduced an innovative assembly line approach to building Generative AI applications, paired with the unique Large Language Model “RosettaStoneLLM.” This targets regulated sectors like finance, insurance, and legal services. This novel approach is set to transform AI application development, focusing on automating complex workflows that require human-like cognitive decision-making.

Despite the excitement surrounding Generative AI, its adoption in enterprises has been slower than anticipated. Many AI initiatives stall at the prototype phase. Enterprises face a tough choice: invest heavily in building their AI systems or risk exposing sensitive data using external models. This issue is especially acute in highly regulated sectors where data security and compliance are critical.

Many enterprises face the challenge of transforming large volumes of structured data, such as database exports and spreadsheets, to align with their internal workflows. Converting millions of CSV files and Excel spreadsheets daily, this traditionally manual and costly process racks up billions in yearly expenses for large organizations, particularly in sectors like insurance, healthcare, and finance.

As part of its “assembly line” engine for AI Solutions, Hercules is releasing the first enterprise-grade LLM of 7 billion parameters that “speaks” with spreadsheets, called “RosettaStoneLLM.” It has been trained on a vast amount of data to perform tasks like mapping, transforming, and verifying structured data.

“Over the past eight months, in collaboration with our clients and partners, large consulting and Insurance companies, our team has been focusing on merging top-tier structured data transformation expertise with the capabilities of our Hercules engine,” stated Alex Babin, CEO of Hercules.

The results on enterprise datasets demonstrate that “RosettaStoneLLM” outperforms general models like GPT-4 by 10% to 30% in tasks like entity mapping and code generation for data transformation, both in processing speed and output quality.

Hercules’ assembly line method, combined with a set of vertically oriented models, addresses the challenge of enterprise-grade, scalable, and reliable AI solutions within the enterprises’ existing security perimeters. The company’s innovative approach has led to a 5x annual growth and partnerships with numerous Fortune 500, insurance, and financial services companies and some of the top law firms in the US.

About Hercules’ ’Assembly Line’ and “RosettaStoneLLM”:

  • Assembly Line for AI Applications: Hercules transforms enterprise AI application production by emulating the manufacturing assembly line. Each application addresses complex business processes, replacing custom-built AI solutions’ slow, unpredictable nature, thereby ushering in a new era of speed, quality, and scalability.
  • RosettaStoneLLM – The Rosetta Stone for Structured Data: Hercules’ new Large Language Model is designed to manipulate large structured datasets like spreadsheets and database exports.
  • Impact Across Industries: Hercules’ innovations are already making significant inroads in various industries, streamlining processes like insurance policy processing, financial data analysis, and invoice reconciliation.
  • Cost-Efficiency and Enhanced Productivity: By automating and optimizing data conversion processes, Hercules’ solutions are set to save billions for large organizations, unlocking growth and innovation.
  • Rapid Deployment: Integrating prebuilt components, LLM models, and data ontologies means deployments can be completed in days or weeks, maintaining high standards of quality and security.


As Hercules continues to enable enterprises to horizontally scale AI solutions, it is transforming the future of work across all industries. For more information about Hercules, please visit www.hercules.ai.



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 Hercules
 Ai
 Rosettastonellm
 Zero Systems
 Large Language Model


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