Earning Trust Without Showing Your Data to a Rival

1. Introduction: A Promise Made

The first post, where we looked at why TradeLens died, ended with a question: Is it possible to build trust without sharing data?

Start with an everyday example. When you hand your driver's license to a police officer at a traffic stop, the officer's only goal is to confirm you're authorized to drive that vehicle. But the moment they hold the license, they also see your national ID number, your birthplace, and your date of birth — when the only thing they actually needed to know was "authorized to drive this vehicle."

In logistics, exposing data you don't actually need to share costs a lot more. By the end of this post, you'll see what could change in your own business.

2. What Happens Today?

Imagine you're a company exporting from Turkey. You have to prove the origin of your product, or that it complies with certain standards. When a buyer or an auditor asks for documents to verify the rules, you may end up having to share your supplier information, invoices, or cost details.

The document solves your operational problem, but it brings a commercial sensitivity along with it: while you only wanted to prove compliance, you end up exposing more data than necessary — your cost structure or your supply network, for example — to the other party. Over the long run, this creates unnecessary data exposure that can weaken your hand at the negotiating table.

3. What Changes With This?

This time, the same exporter only proves the claim "this product was manufactured in this country, to this standard." The supplier, price, and quantity information stay with them.

This method is called a zero-knowledge proof (ZKP): proving that a claim is true without revealing the underlying data it's based on to the other party.

Think of a sealed note. The other party doesn't see the content of the document — only the sealed note confirming the claim — and they can verify whether that note is genuine. Behind the scenes, the exporter generates a proof, and the buyer verifies that proof.

4. Who Sees What?

• The buyer: instead of seeing the supplier list and prices, they only see the result "origin confirmed."
• Customs: instead of seeing the entire document set, they only see the result "document valid."
• The exporter: keeps their secrets to themselves instead of disclosing them.

5. Where Else Could This Be Useful?

• Customs documents: You can prove a document is valid and complete without opening up its commercial content.
• Cold chain: You can prove that temperature stayed within a defined range throughout the journey, without sharing every single measurement record. Researchers are exploring this idea for perishable goods, but there's no working system yet.

These are potential use cases, not applications that have become widespread yet.

6. Where Does This Stand Right Now?

I didn't want to skip this part, because I set a big expectation at the end of the last post.

Academic work still describes this field as "early stage." The examples built for proof of origin — OreProof, designed for gold supply chains, and PrivChain, which gives origin information without revealing a product's exact location — are both prototypes. There's no system working at scale yet. Using this isn't free, either. Connecting it to your existing systems requires custom software and expert support. And there are no shared rules yet for customs authorities and banks to officially accept this kind of proof.

7. The Practical Takeaway for a Logistics Professional

You don't need this for every business. If you work with a single, trusted buyer, or if an auditor's certificate is enough, today's method works just fine.

This idea might be worth something to you if you answer "yes" to these questions:

• Does the information I'm forced to disclose carry value to the other party, like a competitor?
• Am I performing the same verification over and over for many different parties?
• Could the other party become my competitor tomorrow?
• Isn't an auditor's certificate enough for me?

If you answer "no" to all of them, your current method is working just fine.

8. The Question Left Behind

But what if the temperature sensor measured wrong? Or what if the person who entered that first piece of data into the system cheated? What good is a flawless mathematical proof if all it does is flawlessly prove data that was wrong from the very start?

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This post was originally published on LogisticsIQ.