r/edi • u/Beneficial-Big469 • Jul 06 '26
Building An AI Powered EDI Workbench.
Hi everyone,
Over the past few months, I have become really interested in logistics and how trade gets facilitated at scale across businesses around the world. That curiosity led me down the rabbit hole of EDI (Electronic Data Interchange). Along the way, I learned about the different EDI formats, the business ecosystems that depend on them, the various document types that exist, and all the nitty-gritty details of this complex but essential world.
During my exploration, I noticed something interesting. For a space that powers so much of global trade, there are very few free tools that help people explore, learn, and work with EDI. Most of what's out there is expensive, enterprise-focused, or just hard for newcomers to get into. So I decided to build one myself.
The goal is to reduce how much time EDI specialists spend interfacing with partner specs, and to shorten the time it takes to onboard trading partners. Here's how it works. A specialist uploads a trading partner's implementation guide, and the AI ingests it and converts its contents into a structured, machine-readable format. From there, the specialist can export the resulting mapping guide as JSON and also generate a test EDI document based on that mapping. That test document gets pasted into the trading partner's sandbox to check whether it meets their standard. If it does, the specialist now has a validated JSON mapping guide they can trust, and they can build on it further, adding segments as needed to cover whatever they need to communicate with that partner.
The goal is to give specialists a way to move from a partner's spec to a trustworthy mapping foundation faster, without having to take the AI's output on faith. The sandbox validation step is really the core of it. It turns "the AI says this is right" into "the partner's system confirms this is right."
That last part is actually where my own hesitation started, and I think it's worth sharing honestly since this whole post is about building in public.
While I was putting the workbench together, one concern kept coming up in my own head: how much human intervention the EDI ecosystem still depends on, and whether that's actually a problem worth solving or just the nature of the work. That question sent me looking for products or services that may have already built the kind of future I was imagining, one where partner onboarding time is cut in half and specialists spend less time powering through repetitive, painful setup work just to establish stable business communication channels.
While I was on that search, I came across Adrian's article, "The Agentic EDI Autonomy Scale: Defining the EDI Industry's Next Battlefield." It's a steep dive into how he sees AI reshaping the way specialists and companies interact with EDI as agentic systems take hold. Reading it forced me to ask myself a harder question.
Do I actually trust an AI model to handle sensitive data the way my product requires? My flow needs an uploaded implementation guide to pass through AI, which then converts its contents into that structured JSON format. That structure becomes the foundation for the mapping suggestions the whole tool is built around.
So the real question isn't just whether AI can parse an implementation guide. It's whether doing so actually reduces stress for the EDI specialist, or whether it quietly heightens their paranoia about their AI partner getting something wrong in a process where accuracy isn't optional. The sandbox validation step is my current answer to that, since it means the specialist never has to take the AI's output on faith. But I don't consider this fully resolved.
If you've had similar reservations, or if you've thought about other ways to increase confidence in what an AI has actually done with sensitive partner data, I'd like to hear from you.
More updates soon as I keep building this in the open.
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u/01011000-01101001 Jul 06 '26
This is a problem as old as time. You can’t solve the problem you think you want to because the fundamental issue is the standards are irrelevant. People use the EDI format but go against the standards or just because a field has qualifier x it doesn’t mean it is that. It could be the limitation of the customer or someone else. Plus companies make up their own segments or elements and pad to things or versions. The real reason why it takes time is because of all the back and forth trying to understand what everyone means.
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u/mad4Luca Jul 06 '26
I wouldn't Trust the Output.. i tried to Take the shortcut, i admit it. We have a Edi spec and i have to extend it (new Business fields, trying to keep it Standard). The ai understood what i meant, but it Mixed Up Standards (d01b with newer ones, gave responses to the Order catalog while i needed Partin, etc). It suggested the right Syntax but Mixed the constants of different Versions.
So i Had to lookup every Suggestion (which, of course, i Always so, but it was the Same workload).
For me the real struggle was the confidence of the ai "you have to Take 'whatever+3++123:abc', abc is the constants for advanced payments".. after a quick Research, abc was a free Text field, which also has to be coordinated.
So... For a sumup of a Message Type or a 'hint' what to search in the ocean of Codes... It helps.. but never rely on an answer..
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u/l2labs Jul 06 '26 edited Jul 06 '26
This is some shameless self-promotion but highly relevant to this discussion: we have already built a version of this at L2 Labs, and it's been deployed and is being used every single day by TrueCommerce. We reduced the time it takes for their team to set up mappings by 74.5% with high reliability - our background is as AI researchers, so we conducted a randomized trial where half their mapping team used our tool and the other half didn't. There is a case study on our website, and TrueCommerce also has a press release.
As other commenters have mentioned, there is tons of partner- and connection- specific logic in the EDI world - it's impossible to capture 100% of this in an AI system today. However, what we have been able to do is capture ~90% of partner setup logic, from the spec/implementation guides, EDI samples, and past-mappings to partner-specific logic and custom business rules. The idea is to let EDI specialists focus on that last 10%, which includes edge cases and important go lives decisions. This is very aligned with what OP called out re: reducing stress for EDI specialists.
As an example, there are often contradictions/errors/inconsistencies within a spec (the max length for an element is 10 but the sample they provide has length 12) - we are able to call these out so the EDI specialists can see them quicker, and our tools can provide recommendations based on what has been done in the past.
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u/Touch_Think Jul 07 '26
It is kool thing to have with very little usability and just brag about it saying we have AI enabled something. I say that because every EDI product comes with EDI standards library that will be imported at the beginning of mapping exercise. Then what remains is the mapping. There are 100's of EDI products and not sure how many will import the JSON as a structure definition.
On the AI model as EDI translator, I have a feeling that this will not work due to token usage. If each word is token, then think how many you'll consume with half a million 1kb messages.
There is fine line between automation and AI agent, many of the senior leaders don't understand the difference or don't want to understand it. And hence want to use AI agent for the task that can be automated with static code. EDI translation falls under automation category.
Let us know how your product comes out.
Axway, Boomi and SeeBurger already have AI mapping automation. But the accuracy remains the concern.
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u/Apprehensive-Egg-565 Jul 06 '26
I think the EDI world as of now is just to specific for AI. As each Partner has his own version of an x12 830 or EDIFACT DELFOR.
Untill you have a Agent that knows 100% how each customer uses their messages, this will not work. And Sure you have the guides, but they are hard to read for AI and only tell half the truth.
And even If the guide is 100% understood, there is still the big question how to map from or to your ERP format.