TRACE

In global commodity trading, documentation errors and delays are a persistent bottleneck. Each shipment requires dozens of interdependent documents, such as the sales contract, Letter of Credit (LC), Bill of Lading (BL), and packing lists, that must be prepared across departments like operations, shipping, accounting, and sales, often spread across multiple countries and time zones.

This fragmented workflow causes:

Frequent human errors in values, quantities, and compliance fields
Missed deadlines due to timezone and dependency lags
High training overhead-junior staff require months to master document logic
Inefficiencies that lead to financial loss when shipping or LC timelines are missed

To validate the need for Trace, we conducted over 50 in-depth interviews with stakeholders across the global commodity supply chain, including traders, logistics heads, operations managers, and documentation officers from firms such as Mayar Group India, Olam, and other mid-sized exporters. Our findings revealed that despite widespread use of ERP and spreadsheet tools, documentation workflows remain highly manual and fragmented, with teams operating across different countries and time zones. Errors in Bills of Lading, Letters of Credit, and packing lists often led to payment delays, demurrage costs, and compliance risks. These insights directly shaped Trace’s focus on automation, validation, and cross-department visibility. Based on this research, we secured a design partnership and Letter of Intent (LOI) with Mayar Group India, validating early market interest and confirming Trace’s relevance in real-world operations.

Competitors

Through multiple rounds of brainstorming and rapid prototyping, we explored different dashboard layouts, document flows, and brand identities, refining Trace from a concept about “error reduction” into a seamless, AI-powered workflow that connects every team in the trade ecosystem.

We conducted user testing sessions with traders, operations heads, and documentation managers to evaluate Trace’s usability and real-world relevance. Participants were asked to complete core tasks, such as generating a shipping document, tracking timelines, and validating entries across departments. The feedback highlighted that users valued the platform’s clarity, automation, and visibility across teams, but wanted more intuitive signifiers and clearer next-step prompts. These insights guided iterative improvements in layout, dashboard navigation, and the AI-driven alert system, ensuring Trace fits seamlessly into existing workflows while reducing manual friction.

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