AgenticOS (AI) for End User
An agent that acts on what it finds in your PLM.
Where a part is used. What changed on a BOM. What is blocking a change. Ask in plain language — it answers, then drafts the summary, builds the list, files the report.
- Runs on Aras Innovator
- Scoped to your own permissions
- Grounded in live PLM data
- No training on your data
- Answers plus artefacts
It only ever returns what you already have permission to see.
Whose question is it
The question changes at every desk. The studio doesn’t.
A design engineer, a quality lead and a planner open Aras Innovator for completely different reasons. None of them has to learn anyone else’s vocabulary, or anyone else’s screen.
Who is asking
What they open Innovator to answer
What comes back
Design engineer
About to change a part
“Where else is this part used, before I change it?”
Every assembly that references it — live, and attachable to the change.
Quality engineer
A deviation just landed
“Which built lots does this change affect — and have any shipped?”
The affected lots, and which of them have already left the building.
Manufacturing planner
A change lands next week
“What does this change do to the parts we buy?”
Buy parts added, removed and revised — with the change behind each one.
Programme manager
Status call in an hour
“What is holding this release, and whose desk is it on?”
Open items on the release, grouped by whose approval they wait on.
Supply chain
A supplier has gone quiet
“If this supplier stops, which assemblies stop with them?”
Every part that lists them as an approved source, and what sits above it.
Five questions. One studio, answering all of them the same way.
Live, not a copy
Read from Aras Innovator at the moment the question is asked.
Your account, not a new one
Scoped by the Innovator permissions each person already has.
A person still decides
Anything it would change goes to your existing workflow and approvals.
The answer, not the navigation
Find it, analyse it, act on it
Three verbs, in order. Finding it is where this starts, not where it stops — the answer is read live from your environment, and it carries through into the work that follows.
Find
The thing you opened Innovator to look for, without knowing where it lives.
Find anything
Parts, BOMs, documents and changes, asked in plain language. No query syntax, no navigation tree, no saved search to maintain.
Find where it is used
The question people actually open PLM to answer — asked once, instead of clicked through four levels of structure.
A plain-language question, and the live rows the answer is built from. Analyse
What the result means this week — which is the part a search box has never been able to do.
Understand status
What changed on this BOM, what is blocking this change, who is waiting on whom — read from the record, not from somebody's memory.
Summarise
A dense BOM, document or change turned into a few sentences a non-specialist can act on without opening it.
Something dense, next to the summary the studio wrote from it. Act
The answer turns into work — inside the workflow you already run, not beside it.
Take guided actions
Approvals unchangedStart work, route it, raise the change — through the same workflow, past the same people, with the same sign-off.
Get artefacts
A where-used report, a summary, a list — generated with the answer and attachable to the record, not instead of the answer.
A drafted action, and the approval it has not passed yet.
And all three only ever reach what your own Aras permissions already reach.
Not a filter applied to the three columns above — the condition they run inside. The section below shows how.
AgenticOS (AI) — the agentic AI platform for enterprise PLM
The operating system for enterprise AI agents — where they are configured, governed, and run inside your PLM. Configure agents for development, quality, and everyday users; chain them into governed workflows; bring your own model; and keep every action permission-aware and traceable — across Aras and 3DEXPERIENCE.
- Bring your own modelPlug in any model, cloud or self-hosted — no lock-in, and you decide where your data goes.
- Permission-awareAgents inherit each user’s PLM security — they only see and do what that user is allowed to.
- Grounded in your PLMIt connects and grounds itself in your data automatically — no manual training of your environment.
- Governed by defaultEval, registry, approvals, history, traces, dashboards, and token controls — built for admins, not bolted on.
Safe by design
Nothing new to secure. Nothing new to build.
Both of those come from one fact: it inherits what you already run. Your Aras permissions, per user, per session, so there is no second access model for someone to keep in step with the first — and your live environment as it stands at the moment of the question, so there is no index to build before anyone gets an answer. The quickest way to prove the permissions half is not another paragraph. It is two people asking the identical question and getting different answers.
Scoped to your own permissions
Inherited from Aras, per user, per session. Not a second access list for someone to keep in step with the first.
Grounded in your real data
Answers come from the live environment as it stands at the moment of the question — not a copy, not a nightly index.
No training on your environment
It grounds itself in what is already there, so there is no training project to fund before anyone gets an answer.
Answers plus artefacts
A report, a summary, a list — generated with the answer and attachable to the record, so the work leaves a trace like any other.
Let’s make PLM answerable
Give Every User a Faster Way to Work
See the end-user agent answer a real everyday question on your own Aras Innovator — returning a plain-language answer, a generated artefact, and only the data that user is allowed to see.
FAQ
Frequently Asked Questions
No — it inherits each user’s PLM permissions and only returns what that user can already access.
No — it grounds itself in your PLM automatically, so answers reflect your real environment from day one.
A plain-language answer plus any generated artefact — a summary, a report, a list — and, where the process requires it, guided actions that respect approvals.