Agentic AI
Autonomous Finance
Why Agentic AI in Order Management Isn't Just Another Trend
Find out how agentic AI eliminates inefficiencies in order management and transforms financial operations.
In our previous blog "OCR, Agentic AI or Both?", Brian Shannon shared key differences between OCR and agentic AI and how they impact automation, accuracy, and efficiency in finance. Today, as promised, Brian returns to reveal how agentic AI is fundamentally revolutionizing order management and finance processes through real-world applications that are leaving traditional systems behind.
Brian: Technology and especially AI is changing rapidly. In the past two years we’ve seen huge leaps forward. At Hypatos, we are on the edge of development and dealing with new things every day, so I can appreciate that, for a practitioner, they could feel overwhelmed or intimidated. They could also feel excited about the possibilities that agentic AI brings. Quite frankly, we’ve got people in the area of Finance that probably have more of a fear of missing out than a fear of losing their job.
Brian: Let me outline the three most pressing issues that agentic AI can address:
#1 Quality throughput: People are people. And we don’t always operate at the same level all day every day. Monday morning is going to be a lot different than Friday at 5pm. We used to joke that no-one wanted the car that rolled off the production line on Friday at 5pm until agentic AI provided greater consistency of quality and throughput.
#2 Knowledge availability: There is a lot of inherent intelligence in the individuals who are processing orders and if they happen to call in sick, go on vacation or whatever, you may get different and varying results from the person who is standing in for them. With agentic AI, it can learn from the knowledge of your best people and it will be available 24/7 if needed.
#3 Processing consistency: There can be a lot of variation in the quality of what is being processed over time, especially with seasonality. The limitations of manual transactions were really put in the spotlight during COVID. Suddenly, paper driven organizations had a real issue processing orders. And if they didn’t adapt – they didn’t survive.
Brian: I think of Order Processing in three dimensions. It’s about timing, accuracy and transparency. And agentic AI helps with all three.
Let’s take timing first. A classic example. A customer places an order, and you want it to go out as soon as possible. Their purchase order might have a mistake on it – for example, the product ID. An experienced data entry clerk may be able to understand and interpret the exception to get the order processed, but if they can’t you have a problem. This brings me to accuracy. In the example I gave previously, the data wasn’t accurate. Exceptions always delay the process. Lastly, transparency. This is particularly important for organizations that might have constrained production. They would need to know: Is there an allocation for the product that the customer ordered? Transparency of information is a real issue when you must stage orders based on what you have in your queue at any given time.
Whether you are processing manually or using AI, these core criteria need to be met for order management to be competitive. I think it is obvious from the example above that when using agentic AI, you will be more competitive.
Brian: A lot of organizations want to use a cataloging process. But catalogs are not perfect. Somebody must maintain the data. Somebody must make sure the pricing is correct and then you have to make sure that your customers are using the correct codes or material IDs etc.
Different industries have different requirements and feel the pain differently. Some more acutely than others. Highly configurable products require instant access to data, for example, more so than commoditized, generic products. The complexity determines how much or how little a human is required in the loop.
Brian: In a nutshell, yes. I believe finance individuals want to be adding value in the process. They want to be doing strategic work.
Brian: All agentic AI solutions use a large language model for training purposes. The difference with Hypatos is that we have a proprietary language model too that is unique to the customer. In this model, we are essentially building a database of history, information and intelligence that pertains to the customer. This is what provides the context, and a higher degree of accuracy. Over time this library of knowledge becomes hugely valuable to the customer.
We focus on intelligent document processing. We don’t focus on the workflow around the order management process. Our approach is to work within an ecosystem and integrate with partners that have a core competency that is complimentary to ours. We do the same for eInvoicing and accounts payable too.
With our approach we can capture, contextualize and effectively process documents, whether they originate on paper, PDF or other electronic formats. We operate with the majority of ERP systems in the market – vendors such as SAP, Oracle, Workday. We also have a powerful API interface which means we can operate with all ERPs where we don’t already have a custom connector developed.
In summary, the Hypatos solution is highly dynamic and offers significant autonomous capture accuracy right out-of-the-box (in many cases 85-100%), unlike traditional OCR systems which require extensive training and ramp-up time. Our solution also provides a BI tool called Insights that enables customers to be alerted to anomalies and trends such as underperforming customers or vendors or compliance issues.
Hypatos enables data entry clerks to become knowledgeable experts who can understand and rectify situations, thereby improving customer satisfaction.
Brian: Very little. We have tried to make the process of implementing Hypatos and integrating it into an existing environment as seamless as possible including considering legacy processes, technology and implementation. We collaborate with industry-leading experts and trusted partners, including the Big Four accounting firms along with other top-tier organizations.
Often a lot of manual processes still exist and there may be an absence of workflow solutions. This is where we can work with our partners to provide advice and guidance.
Brian: Our projects are measured in weeks or short months but not quarters of years. This is an important factor from a risk perspective. With the standard connectors to major ERP systems and the APIs that exist for all other ERP systems, we can be up and running in a short space of time. We are focused on intelligent document processing, with the emphasis on intelligent, not the workflows surrounding them. These are managed by our partners.
Brian: It is natural to think risk exists when implementing new technology. We have plenty of proof points and metrics from happy customers who see the business value and we are happy to share this.
For example, one of our clients, a leading European supplier of construction materials partnered with us to tackle PO-based invoicing challenges. With 96% of supplier data identified instantly and 91% of invoices matched to POs without extra validation, they've reduced delays and manual reconciliations. The implementation of eInvoicing solutions, designed to comply with German regulations, positions this industry leader to excel in the German market through enhanced operational efficiency and transparency.
If anything, we see a greater fear within companies that data entry clerks will lose their jobs because they don’t know enough about AI to work with it. Many global companies, especially those with shared service centers are trying to automate and deliver greater business value.
Brian: Organizations that have a lot of complexity in terms of procurement–complexity in terms of volume of documents and differentiation within any given order. For example, defense contractors, large manufacturers, consumer products–Fortune 500 and Global 1000 organizations. Mid to large organizations that are processing at least 100,000 documents per year should contact Hypatos.
Brian: I think there are four core benefits:
#1 Reduce Cost: A lot of organizations are looking to trim costs or grow without increasing the total overhead costs. Many companies that I’ve spoken to are looking to double or triple in size within the next three to five years and they would like to do it with minimal cost overheads.
#2 Mitigate Risk: The ability to be more adaptable and flexible, ensure the integrity of data and processes, and be able to use this data to triangulate and provide answers when they are missing. Corporate transformation is constant. How easily can you assimilate a new business and all that entails, for example?
#3 Improve Cash Flow: Orders need to be processed as quickly as possible to start the invoicing as quickly as possible, to get payment. If anything goes wrong in the order process, it can impact delivery, invoicing and the cash collection process, not to mention customer satisfaction.
#4 Process intelligently: As we’ve discussed, agentic AI can capture, triangulate and apply logic to delivery an intelligent answer. It can also handle foreign languages and different formats well too. So, if you get an order in Japanese, agentic AI will be able to take it and convert it into English.
With agentic AI, the benefits for Finance are remarkable. For more information, come and speak with us.
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