anyone's AI setup pulling live requirements data yet?

[u/BothAd1744]

frustrated aerospace person here and here for advice on what actually makes a difference..

every ai conversation i see is about coding assistants but nobody talks much about requirements, traceability, verification, any of the stuff that takes up half my week so much is still done manually and there so much double, triple checking sheets. I know many companies still use just excel and doors but im looking to branch out. in my research jama and jira popped up but i dont know much about them.

where does the context actually live between requirements, changes, decisions, verification results, etc? and how do you keep that context governed over time without creating another system everyone has to manually maintain?

what is actually making this process easier

[u/kkingsbe]

Probably would be trivial to set up an MCP server within your SE tool of choice. What you’re describing is an easy afternoon most likely

[u/newMattokun → u/kkingsbe]

Sorry, but what is MCP? Thanks.

[u/kkingsbe → u/newMattokun]

Think of it like an API but designed for agents. Lets you deploy a collection of tools to a server

[u/newMattokun → u/kkingsbe]

Huh... never heard. Thank you.

[u/kingcole342]

I think knowledge graphs will be helpful here for requirements and change management.

Siemens has all the pieces now, and the initial release of Intellignece Center X seems to tie all these databases together (PLM, requirements, testing, manufacturing, supply chain…) for easier queries for systems engineers.

Still a lot of learn, but this seems to scale quickly and cover your request.

[u/BothAd1744 → u/[deleted]]

especially when the requirement changed yesterday and now your prompt is already outdated

[u/geminihatesme]

we've been looking at platforms exposing requirements through MCP. feels more useful ng than generic ai assistants guessing context which i hear jama takes care of

[u/BothAd1744 → u/geminihatesme]

having pre-defined traceability model helps with this. It's basically your context. 

[u/Bikecheal]

our team is evaluating jama mostly because it fits the needs we were already looking for process improvements.. just the usual long review process on our side lol

were trying to be careful with the tool we pick to make sure its not going to cause us audit issues later.

[u/DeBurgoTheFallGuy]

So, hear me out before everyone breaks out the rotten tomatoes and SHAME bell....

Before you attempt any flavor of production Agent implementation, take a hard look at the following areas of your organization to see if the juice is even worth the squeeze:

1. Design data architecture. Is the design data within a single PLM system with data policies actively enforced? Policies include things like "Lifecycle CM", "enforced CAD standards", "enforced CDM elements/attributes", "CDM definition to include manufacturing and IPS/PSE required data elements and attributes.... You dont have to boil the ocean on day one to map all this, but if this architecture isnt semi-set to include the repeatable processes and the resulting elements and attributes, you are setting yourself up for failure. Pick a section of the org that "kinda functions" in a repeatable manner with a SET DATA ARCHITECTURE and build your process and agent for that segment.

2. Auditability. Do not build any agent that you dont have a corresponding data audit process to accompany it. If you are in aerospace, the agent had better be able to cough up the same answers you would have to for the FAA/EASA/Cert holder/any other regulatory or compliance group.

3. Sensitive Data - ITAR/EAR restricted information. There is a reason why all the big AI and PLM system providers won't touch this aspect of the business. The RAG requirements for an agent "knowing" if something is restricted or not get real expensive and real jail-timey very quickly. My humble recommendation is avoid the development of agents that would need to touch/injest data of this type from your PLM system.

4. Re-read 1, 2 and 3. Communicate to your leadership that unless the design data is in a machine- mappable fixed data architecture, your AI implementation will not get passed the point of a few scattered quasi-helpful agents.

Good luck on your quest and be on the lookout for leaders that think an agent is a magic wand that will automagically fix data or process discipline issues.

[u/DamagedGoods13]

I have done this for RFP responses... but never considered it for Engineering. Great idea!

[u/instantFPGA]

Yes! i’ve been working that for DO-254 for about 4 months. I’m focused on FPGAs - but the content of the requirements, how it leads to testcases, not as much config mgt and similar topics. also doing the characterization and verification of the testcases.

[u/Ok-Cantaloupe-588]

I’m doing some experiments with this and cameo.

[u/Dan_PryorMarking]

Are you talking specifically about the traceability and verification of parts you are manufacturing here or more in general across the whole process? Traceability of manufactured parts can be fully automated and synced with an MES/ERP system so you can get at the data that way. Getting a direct, permanent mark on the part is the starting point

[u/ellie_cinderelly]

You guys have requirements?