Problem: Stakeholders in the scrap industry (mills, recyclers, brokers) face inefficiencies in finding optimal partners.
Solution: Build a marketplace that uses AI for real-time matching based on location, material type, and pricing trends, and enables circular, closed-loop supply chains.
~~Why It Works: Solves the pain point of inefficiency and aligns with broader marketplace trends.~~
Initially, we hypothesized that removing middlemen would increase value for manufacturers by eliminating the take rates on which middlemen operate. However, we discovered that middlemen perform crucial services for recyclers, such as processing, aggregation, quality verification, financial risk absorption, and logistics.
Middlemen—often scrapyards—take on the labor-intensive tasks of unpacking, sorting, and preparing materials to meet specific recycler requirements, such as bale size and metal composition. They aggregate supply from various sources and store materials until needed, enabling recyclers to operate at scale and improve efficiency. By absorbing risks associated with market fluctuations, liability, and inventory, middlemen help manufacturers avoid exposure to these challenges. Manufacturers, whose priority is often clearing space quickly, benefit from the prompt payments and streamlined logistics that middlemen offer, whereas end buyers/recyclers typically pay on net 30 or net 60 terms. Additionally, middlemen provide price stability by hedging prices, which helps to mitigate market volatility for manufacturers.
Transactions in the scrap industry are rooted in personal relationships, trust, and face-to-face interactions. Middlemen absorb risks that would otherwise fall on manufacturers, leveraging their expertise to optimize logistics costs, consolidate smaller loads into larger, more marketable quantities, and facilitate specialized, custom-batch processing required by recyclers. This makes their role deeply entrenched and difficult to replace with digital solutions.
In the last few months, we conducted extensive site visits to physically assess, label, and organize available materials. Each step of the process, from direct supplier engagement to meticulous material sampling and in-person negotiations, required a high level of effort and adaptability. This case study outlines the intensive work involved in securing and completing a scrap trade in an industry that prioritizes relationships, trust, and hands-on involvement. Through these efforts, and with guidance from our contractor—an experienced scrap metals trader of over 15 years—we navigated the complex challenges of building a reliable supply chain in a highly competitive, traditionally opaque market.
We began by contacting multiple small manufacturers to source scrap. However, aligning their materials in terms of type, form, and quantity proved challenging. Even when willing to participate, manufacturers provided inconsistent quantities and qualities, complicating the effort to achieve a profitable volume.
Many manufacturers lacked an accurate inventory of available scrap, as managing scrap materials wasn’t a high priority. In one instance, a facility manager overseeing excess inventory estimated that scrap management accounted for “less than 1% of their job." This lack of attention meant that some scrap sat untouched for years.
We conducted physical inventories ourselves, labeling each box, assessing scrap type, and confirming which items were sale-able. Additionally, logistical details, such as whether pallets had pockets (allowing for easy forklift unloading) or fork slots only (requiring manual labor), impacted unloading times and costs.
Alongside these manual efforts, we developed a PostgreSQL database hosted on Supabase to organize and streamline the process of connecting manufacturers with potential buyers. This database was designed to centralize supply data, enable buyer matching, and support future automation, by laying the groundwork for integrations with tools like Mapbox for logistics visualization and route optimization.
During the development of the database, several challenges emerged that highlighted the complexities of digitizing the scrap industry. Manufacturers often lacked accurate scrap inventories, which necessitated significant manual intervention to verify and input data into the system. Additionally, the descriptions of scrap materials varied widely, posing difficulties in standardizing the data for effective matching between suppliers and buyers. Compounding these issues was the proprietary nature of industry data; manufacturers and middlemen were often reluctant to share information, viewing it as a competitive asset. These challenges underscored the limitations of relying on digital systems alone and emphasized the need for a hybrid approach that integrates manual processes with digital tools.
pain point: inventory blind spots and reluctance