AgenticOS (AI) for Implementation
An agent that already knows your PLM
The AgenticOS studio for the people who build your PLM — configured to your standards, grounded in your environment, governed by your approvals.
Your model. Your permissions. Your rules.
- Aras Innovator & 3DEXPERIENCE
- Bring your own model
- Configurable agents & workflows
- Respects PLM permissions
- Eval, approvals & full traces
- Grounded in your PLM data
What it changes
Do more. Spend less. Go live faster.
Every change checked by tooling and signed off by a person — on Aras Innovator and 3DEXPERIENCE.
What moves
Less cost
Cost corner
Senior time goes on the review, not the first draft.
More scope done
Scope corner
Every release carries more of the backlog.
Faster ROI
Time corner
Changes reach approval in days, not release cycles.
Better quality output
The middle
Profiler, Q-Checker and SonarLint on every change.
Delivered on both platforms
Wherever you run
One agent, one approval gate — Aras Innovator and 3DEXPERIENCE.
Scopemore of it done
Costless of it, per change
Timefaster to value
Held in the middle
Quality
Checked by tooling. Signed off by a person.
Where it fits
This studio owns four of the six stages
The lifecycle you just saw, with the stages this agent works inside lit up. It picks the ticket up at ALM and carries it to deployment — but its run breaks in the middle, at the one stage that belongs to a person.
ALM
It reads the ticket and every object the ticket points at.
- Scope summary
Development
It drafts the configuration or the code, against your standards.
- Draft
- Its reasoning
Validation
It runs the checks over its own work and fixes what it can.
- Performance Profiler
- Q-Checker
- SonarLint
Approval
A person signs off. Nothing protected moves without it, and the agent cannot ask twice.
Human gate
Deployment
It packages the approved change and moves it to your environments.
- Packaging Wizard
- Import Analyzer
End users
The change is live. What people ask about it afterwards is the other studio's job.
For End User
- The agent moves it
- A person decides
- Outside this studio
What it does
Explain, build, assure
Explain
Fifteen years of somebody else's customisation, read back to you in plain English — with the objects it actually depends on, named.
Which covers
- Explain the unknown
- Find where it lives
A method explained, with its dependencies cited. Build
Configuration or code written the way your team writes it, with the reasoning attached and the regression test that covers it.
Which covers
- Draft configuration & code
- Generate tests
A drafted change and the test that came with it. Assure
Performance Profiler, Q-Checker, SonarLint and the Test Automation Suite run over the agent's own work — it fixes what it can and says what it could not.
Which covers
- Review against standards
- Regression tested
- Work as a workflow
AgenticOS (AI)
Development agent
Sends its own change through all four before a person sees it.
Performance Profiler
How the change behaves under load.
Q-Checker
Held against your quality rules and standards.
SonarLint
Static analysis over the code it wrote.
Test Automation Suite
Runs the regression suite against the change.
What comes back
- Fixed what it could
- Flagged what it could not
- States whether it is release-ready
Then a person approves
AgenticOS (AI)
Development agent
Sends its own change through all four before a person sees it.
Performance Profiler
How the change behaves under load.
Q-Checker
Held against your quality rules and standards.
SonarLint
Static analysis over the code it wrote.
Test Automation Suite
Runs the regression suite against the change.
What comes back
- Fixed what it could
- Flagged what it could not
- States whether it is release-ready
Then a person approves
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.
See it work
See it work on a real ticket
One recording, one live Aras environment, one ticket — from the question to the change sitting at the approval gate. Nothing staged, nothing cut out.
Also in AgenticOS (AI) — for End User
When your change goes live, the people using it get an agent too.
They ask Aras Innovator about what changed — in plain language, from live data, inside the permissions they already have.
Find
“Where else is this part used?”
Every assembly that references it, read live.
Analyse
“What changed on this BOM since the release?”
A few sentences a non-specialist can act on.
Act
“Raise the change and attach the where-used report.”
Through the same workflow, past the same approvals.
Let’s put an agent on your dev team
Give Your Engineers an Agent That Speaks Your PLM
See the development agent explain a real customisation, draft against your standards, and hand off to quality — all on your own Aras or 3DEXPERIENCE environment.
FAQ
Frequently Asked Questions
No. The development agent drafts configuration and code against your standards, but nothing is applied until a human approves it. Work can also be handed off to the quality agent for review and release-readiness checks, and every step, including prompt, reasoning, tools, and output, is traced in the admin panel.
AgenticOS connects to your Aras or 3DEXPERIENCE environment and grounds itself in your data automatically, reading methods, ItemTypes, workflows, and data models, with no manual training required. It inherits the developer’s PLM permissions, so it only sees what that user is allowed to see.
Rabbit Implementation Studio is SteepGraph’s Aras delivery studio, and its AI code review supports quality checks within that delivery process. AgenticOS (AI) for Implementation is a broader development agent that explains existing customisations, drafts configuration and code, finds where objects and rules are defined, generates tests, and hands off to a quality agent in one governed workflow, across both Aras and 3DEXPERIENCE.