Hyperautomation AI drives efficiency and innovation

The rise of AI has transformed how businesses operate, particularly with its latest innovation: generative AI applications. These advancements empower organizations to process and use complex data in previously unfathomable ways. The recent developments in AI, especially in hyperautomation AI, are paving the way in which for remarkable levels of efficiency and innovation.

“We just posted a few of our greatest growth results we’ve had in our history,” said Andrew Joiner (pictured, left), chief executive officer of Hyper Labs Inc. “So we’re excited in regards to the growth. But behind that growth are some product announcements [and] some leadership recognition from a few of the leading analyst firms.”

Joiner and Mayur Pillay (right), vp of corporate development at Hyperscience, joined Shelly Kramer, managing director and principal analyst at theCUBE Research, to debate the impact Hyperscience’s recent product innovations are having within the hyperautomation AI arena. (* Disclosure below.)

Innovation results in rapid growth and industry recognition

Hyperscience has experienced unprecedented growth previously few months, achieving significant milestones that underscore its prominence within the generative AI arena. The corporate’s innovations have recently earned it a “Leader” status in reports from two notable industry analysts.

“We achieved a leadership status with Forrester and IDC, who’re covering our market in numerous terms: one (is) document mining and the opposite [is] called [intelligent document processing],” Joiner said. “We’re excited in regards to the growth we’ve with our customers overall.”

Hyperscience’s growth isn’t just in regards to the numbers; it’s also in regards to the progressive products the corporate is bringing to the market, Joiner observed. The corporate’s most recently introduced solution, Hypercell for GenAI, extends the corporate’s capabilities in hyper-automation AI. The answer uses advanced AI models to read and process human-friendly information, providing businesses with tools to administer complex, mission-critical documents with a deal with governance, transparency and security.

A ‘human-in-the-loop’ approach to hyperautomation AI

Unlike traditional generative AI applications, which create prose and human-friendly information, Hyperscience’s approach focuses on reading and understanding this information, based on Joiner. This method equips organizations with the flexibility to automate previously manual and labor-intensive processes, unlocking substantial value from the information firms already possess.

“We use models to essentially read human-friendly information, and that’s really the alternative of generative AI,” he said. “Generative AI uses very powerful frontier models to generate prose and human-friendly information.”

Joiner explained the advantage of Hyperscience’s approach, saying, “We’re in a position to access very complex, mission-critical documents which might be embedded within the core of the enterprise, and admittedly, many of the stuff has not been automated by businesses.”

This capability is crucial for businesses that depend on data embedded in documents akin to purchase orders, invoices and statements. By providing a bridge between this critical data and frontier AI models, Hypercell for GenAI allows enterprises to harness the complete potential of knowledge. The product’s ability to deliver this data accurately and efficiently to AI systems paves the way in which for brand spanking new business opportunities and applications.

Pillay noted that partnerships with Google Cloud Platform and Hewlett Packard Enterprises Co. enable Hyperscience to “provide a type of end-to-end development platform.” Enterprises can herald propriety data but “bring it in a way where it’s accurate, where it’s labeled and it’s able to be utilized by AI systems, after which actually deliver gen AI experiences which might be grounded within the language of the business.”

The challenges and rewards of adopting hyperautomation AI

Adopting hyperautomation AI capabilities opens the door to ample recent opportunities for organizations but in addition brings challenges. While the potential for automation and efficiency is important, organizations often face hurdles in integrating these technologies into existing workflows. Hyperscience addresses these challenges by providing solutions that eliminate friction and exhibit a provable return on investment, an important factor for widespread adoption, based on Joiner.

“The chance that we see is vast because that is mission-critical data that’s embedded, that actually they run their businesses on, and we’re in a position to eliminate quite a lot of friction that’s contained in the company,” he said. “We have now a provable ROI that we are able to deliver back to the enterprise and that’s been missing from the generative AI conversation.”

Furthermore, the importance of knowledge as the inspiration of AI can’t be overstated. Citing three stacks organizations need to deal with to deploy generative AI — compute, model and data — Pallay noted that while many large software firms are investing heavily within the compute and model stacks, the information stack is proving tougher.

“On the model stack side, you could have all the inspiration models which were developed, the multi-billion parameter models,” he said. “But while all that’s really complex, there’s quite a lot of complexity in the information stack and that’s getting your whole data ready to really be utilized by AI applications.”

Generative AI heralds a full platform shift, Joiner explained. The technology offers the chance to reimagine the software organizations use day by day, he added.

“I’d encourage businesses to lean into the generative capabilities,” he said. “I feel businesses that use AI will replace the companies that don’t. I feel they should lean into it, and I feel this can be a transformative time and exciting time for all of us.”

Here’s theCUBE’s complete video interview with Andrew Joiner and Mayur Pillay:

(* Disclosure: Hyper Labs Inc. sponsored this segment of theCUBE. Neither Hyperscience nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE