Developing AI solutions that align with industry demands is a complex process. Cesar Ricci, founder of Centaurea Professional Logistics, recently announced PlugComex, an AI-powered platform designed to streamline operations for the international logistics and shipping industry. In this article, he shares his insights on creating customized enterprise AI software.
I began training AI for shipping and logistics in 2020. Our company was in a dire financial situation during the COVID-19 lockdown. With international shipping impacted, I had to lay off the entire team.
Then, a new customer approached with a request. They couldn’t have anyone in the office during the pandemic, and needed a system to monitor their import in real time. This need became the catalyst for developing the solution.
Once the software was implemented, the customer saw significant profits, prompting us to invest further in AI development for the industry.
In 2023, with the support of Microsoft’s Founders Hub, we launched PlugComex, an AI-powered solution to streamline operations for international exporters to Brazil and importers within the country.
The need for such a solution was clear, as international trade is full of challenges. Shipping goods can face delays due to incorrect documentation during customs. In Brazil, even a minor invoice mistake can detain cargo for weeks because of errors in VAT calculations or currency discrepancies.
Our AI system minimizes such delays, streamlines documentation handling, and improves the overall efficiency of global shipping. The customized solution we built provides real-time tracking, document verification, and predictive analytics, saving businesses millions of dollars.
We decided to focus on customized solutions because developing tailored AI for our industry requires more than a one-size-fits-all approach. The first challenge is understanding each customer’s unique needs. For example, a small shipping line operating in Brazil may have very different requirements than a Canadian oil and gas company.
Also, developing algorithms to analyze invoices involves training the AI to recognize each supplier’s format and content. The AI not only reads the invoice but also checks for discrepancies, such as incorrect tax values, missing data, and errors that could cause customs delays.
The process of tailoring AI software
Here’s a step-by-step overview of how we created a tailored AI solution for the logistics industry and how you can apply this process to any industry:
Understand the customer’s pain points
The first step in any AI software development project is understanding the pain points your customers are facing. In the case of PlugComex, we understood that the major challenge was the delays caused by customs, which were often due to documentation errors.
This step requires a deep dive into your client’s processes and identifying areas where AI can offer tangible solutions. Whether it’s automating invoice verification, tracking inventory, or improving supply chain visibility, the key is to identify the specific issues that the customer needs resolved.
Integrate with existing systems
The next step is to ensure that the AI software can integrate with existing systems. For example, in our case, we had to make sure our AI could communicate with the customer’s inventory systems, financial databases, and even external government databases for customs clearance. Integration with Application Programming Interfaces (APIs) is essential for smooth functionality, allowing the AI to pull and push data seamlessly.
In our case, PlugComex not only integrated with our clients’ internal systems but also connected to global customs databases, allowing real-time tracking of shipments and document verification across borders.
Train AI on real data
AI is only as good as the data it’s trained on. This is why data collection and training are pivotal to the success of any AI system. For us, this meant gathering hundreds of invoices, customs declarations, and other shipment-related documents. We then used this data to train our AI model to recognize patterns, understand document formats, and predict potential issues with shipments.
The process is iterative: every time we received new data from a client, we fed it into the AI system to improve its accuracy. While this process is time-consuming, it’s essential for creating a truly customized solution.
Implement predictive analytics
One of the most valuable aspects of AI is its ability to predict future outcomes. In the logistics industry, this could mean predicting when a shipment will face delays, which documents are likely to cause issues, or when cargo might get stuck in customs. At PlugComex, we used AI to analyze historical data, track trends, and forecast potential disruptions.
For instance, if the system detected an anomaly in an invoice (like a mismatch in the total invoice value), it could predict the likelihood of that cargo being detained at customs. The AI then provides the user with real-time alerts, allowing them to correct the issue before it becomes a major problem.
Focus on usability and training
An often-overlooked aspect of AI development is the user experience (UX). No matter how sophisticated your AI is, if the users can’t interact with it easily, it won’t be effective. We invested significant time in designing a user-friendly interface and ensuring that the AI would be accessible for employees at all levels, from shipping managers to senior executives.
We also provided training sessions for our customers to ensure they knew how to use the system effectively. By making the system intuitive and accessible, we ensured that users could leverage the AI to its full potential without being overwhelmed.
Constantly evolve and improve
Once your AI system is up and running, you should never consider it “finished.” Instead, it’s important to monitor its performance, gather feedback, and continuously improve the system. Over the past three years, we’ve worked closely with our customers, refining the system based on real-world data and feedback.
As the market changes and customer needs evolve, AI systems should be updated regularly to remain relevant and effective.
Overcoming roadblocks in AI development
Developing a tailored AI solution is not without its challenges. One of the most significant obstacles we faced was convincing customers to adopt AI, especially in an industry that was still heavily reliant on email communication and manual processes. Additionally, getting all the data required for AI training was difficult, as many companies didn’t have the right documentation or systems in place.
Another challenge is the time and effort required to train the AI. Every client has different needs, and this means that the AI must be constantly retrained with their unique data. This is why we prefer a consultative approach, where we work closely with clients to understand their operations and fine-tune the AI to their specific requirements.
The future of tailored AI
As AI continues to evolve, the potential for customization will only increase. By continuing to work closely with clients and focusing on their specific needs, we can help businesses unlock the full potential of AI and transform the way they operate in an increasingly complex global market.
If you’re considering developing a customized AI solution for your industry, remember that the best results come from a deep understanding of your customer’s challenges, a flexible approach, and a commitment to continuous improvement.
With the right data, resources, and mindset, you can create AI software that not only solves problems but also drives growth and innovation for your business.
