As we all navigate the transformative impact of Generative AI, large language models have been promising to reshape the way we manage business processes and intelligent document processing (IDP). While the potential of these models is undeniable, the journey from promise to practice reveals several challenges that can only be addressed by integrating them thoughtfully within an Intelligent Automation Platform.
Addressing the Real-world Challenges in using Generative AI
The enthusiasm for large language models (LLM) stems from their ability to find information, generate human-like text, and infer meaning. These can significantly accelerate the automation and enhancement of business operations. However, a closer look at their application in real-world scenarios uncovers challenges like output variability, hallucination risk, and slower processing times (and higher processing costs) when dealing with image-based content.
These challenges underscore the gap between the potential and the practical utility of LLMs in business contexts. The variability of outputs can lead to inconsistencies, affecting reliability. Hallucinations, where AI generates incorrect or fabricated information, pose a risk to decision-making integrity and ability to rely upon AI for outcomes. Moreover, slower processing speeds for content-rich documents can impact business efficiency requirements, creating bottlenecks that negate the benefits of automation.
Bridging the gap between the theoretical capabilities of generative AI and its practical business application requires strategic integration with an intelligent automation platform. TotalAgility represents a prime example of how this convergence can amplify the strengths of LLMs while mitigating their shortcomings.
Here’s How it Works
A cornerstone of this approach is in prompt engineering, which is the skill of crafting precise inputs to guide the Generative AI towards delivering consistent and relevant outputs. This is vital for minimizing the variability of LLM outputs and ensuring consistency across business applications. Equally important is mechanisms to intelligently chunk long form content, which means breaking down documents into manageable sections and ensuring that the LLM focuses on the most relevant data for the task at hand, enhancing the model's efficiency and accuracy in processing and analysis. By presenting the AI with a curated corpus of information, we significantly reduce the risk of hallucinations and improve the speed at which documents are processed. This targeted approach, combined with robust capabilities for validation, and the ability to orchestrate long running processes, exemplifies how Generative AI can be used in tandem with a broader platform to unlock its full potential.
Transforming Intelligent Document Processing with the Copilot for Extraction
The new Copilot for Extraction feature within TotalAgility 8 showcases the practical benefits of integrating generative AI within a broader intelligent automation platform. This new capability in TotalAgility simplifies data extraction by allowing users to describe in natural language what they would like to extract from a document. TotalAgility uses patent-pending technology to manage the process of breaking down content rich documents across multiple channels into machine text, interacting with the LLM, and applying the user’s prompt to return the desired information points. This can work across a high variability of documents, significantly reducing upfront training time, and allowing for a broader range of people to get into the platform and design solutions that involve extracting data from business documents. It also reduces long-term maintenance overhead.
Copilot for Extraction exemplifies the efficiency and scale achievable through this synergy between Generative AI and a broader platform, and it offers a robust pathway for businesses aiming to capitalize on Generative AI's transformative potential while navigating its inherent challenges.
With innovations like the TotalAgility Copilot for Extraction, the future of business efficiency is not just a vision; it's a tangible reality being constructed today. This integration marks a significant step forward in realizing the practical benefits of Generative AI, empowering businesses to advance confidently into the future.
Watch our video to learn more about Copilot for Extraction.
By David Sentongo - Senior Director, Product Strategy
