Commodities are the center of global trade. The food you eat and the coffee you drink all start with agricultural producers. A trader organizes a shipment of it to a receiver near you, who then manufactures and distributes it to your local supermarket or coffee shop.

That sounds simple enough, but any shipment involving commodities involves around 200 processes, at least 50 documents, and extensive coordination through emails and phone calls. The amount of paper and processes is staggering. Errors can be catastrophically costly, ending up with lawsuits over millions of dollars.

Commodity trading companies allocate 40% of their workforce to logistics and operations. It’s a relationship-focused business. These aren't trading firms with Bloomberg terminals doing spot trading with algorithms all day. They are trading actual physical commodities. Many of these deals are agreed on via text message.

Now imagine you're managing thousands of shipments a month. Nearly every trader we’ve talked to can recall a time in the past 6 months where a document or process error resulted in the firm losing hundreds of thousands of dollars.

This led us to explore how we could tailor AI, automation, and collaboration tools to automate the handling of shipment workflows for more efficient operations and accurate documentation. Our team has the background to solve this problem—an ex-sugar trader with 8 years of experience and two engineers with a combined 14 years of experience from logistics and software companies.

There are a few layers to solving the pain points of these customers:

(1) Data Preprocessing: we give them a way to clean up and organize their existing data, which is usually a mess. We help them process documents, classify them, extract relevant fields, organize them by shipments, and search for them.

(2) We use AI and automation to leverage OCR, Multi-Modal Transformers, and indexing methods across 150+ different commodity and logistics document types to automate business processes.

(3) Actions and Workflows: Once the data is processed, we enable users to take actions or kickoff workflows with them, such as entering data into ERPs, using AI agents to compose emails, update freight matrices, track their shipments and predict delays, and more. All of these things are things the user does manually currently and are prone to error, so we automate them to save time and money. An ops team currently spends 60% of their day on these tasks. With our initial product, we are already saving them 2 hours a day.

Our customers so far include one of the largest U.S. agricultural traders, who use our platform to process over a million documents and automate internal workflows, like creating vessel nominations and updating shipment statuses. They also use us to find critical documents quickly. Importers and exporters randomly get audited to make sure the commodity they declared matches what was actually delivered (quality, weight, polarization). These audits can happen years after the shipment, and searching for the relevant documents is a needle/haystack situation. Sometimes they have been unable to find them, and you can imagine how well that goes over with the auditors. We make this easy.

We can’t give HN readers direct access to the product because it can only be used if you have commodity data and that data is sensitive. But here’s a video showing how it works: https://www.youtube.com/watch?v=slOGliSR6IM#t=26s

There probably aren’t too many commodity traders checking HN every day, but we figure some of you have worked as traders or know traders from previous work experience, and we’d love to hear whatever you think about this!