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Hercules AI launches “assembly line” to help companies quickly deploy AI agents

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Hercules AI, a generative AI company innovating around the future of work, has developed a new way to rapidly deploy virtual AI workers across enterprises. Additionally, the company (formerly Zero Systems) launched RosettaStoneLLM, a model that helps companies in regulated industries automate complex workflows that require cognitive decision-making.

Organizations can choose pre-built components to develop and deploy virtual AI workers, which is known as an “assembly line” process. Everything is pre-built, tested and pre-configured – no custom ordering required. Hercules AI says doing so will result in “high-quality, cost-effective and easily scalable” artificial intelligence agents. All that needs to be done is to fine-tune the model so that the robot follows a specified workflow.

Most companies would probably prefer a robot that meets their needs and specifications. However, doing so in a regulated space takes time and money, which can be detrimental to customers. However, the financial, insurance and legal services industries may be more receptive as each component will be scrutinized by regulators to comply with the law and ensure data security. If it works for others in the field, why not follow suit? The only customization allowed is the Large Language Model (LLM).

Another product from Hercules AI is RosettaStoneLLM. It is built on Mistral-7B and WizardCoder-13B and has 7 billion parameters. Companies using this feature can transform structured data in spreadsheets so that artificial intelligence can map and transform it. Imagine the number of database exports and spreadsheets a regulated business might have. Converting these files into useful system-wide data can be expensive and time-consuming. This LL.M. is designed to transform large amounts of structured data into data that fits your internal workflows.

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The company claims that early results show that RosettaStoneLLM can complete tasks such as entity mapping and code generation better than GPT-4’s general model, with up to 30% efficiency.

Screenshot of inference done using Hercules AI's RosettaStoneLLM. Image source: Hercules AI
Screenshot of inference done using Hercules AI’s RosettaStoneLLM. Image source: Hercules AI

As a company spokesperson told VentureBeat: “In the corporate world, especially in areas like insurance and finance, structured data is critical to operations. Consider an insurance company preparing health insurance quotes for customers. Customers submit their HR database information, This information is often in a variety of formats and structures, with unique column, row, and abbreviation naming conventions. Traditionally, converting this data into a format compatible with an insurance company’s internal systems for analysis is time-consuming. However, RosettaStone can This transformation is achieved in just seconds, a task that would otherwise take humans hours to complete.”

Hercules AI, based in Campbell, Calif., has raised $12.1 million in venture capital, and while it doesn’t disclose customer numbers, it does say it is used by Fortune 1000 companies and 30% of the top law firms in the United States.

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