Role-Based Access Control
Agents respect user roles, permissions, and data boundaries so people and agents only access information they are authorized to use.
Read Designing a Governed Manufacturing Agent Workflow
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Connected Manufacturing Agents
Governed AI Agents for Regulated Manufacturing
Secure data. Role-based access. Human-in-the-loop by design.
Connected Manufacturing Agents help regulated manufacturers move from scattered data to coordinated action. Agents monitor signals, investigate issues, gather evidence, recommend next steps, and escalate decisions to qualified humans across quality, yield, maintenance, downtime, and root cause workflows.
They are designed around secure customer data access, role-based permissions, auditability, and Annex 22-aligned human-in-the-loop.
They are designed around secure customer data access, role-based permissions, auditability, and Annex 22-aligned human-in-the-loop.
Customer Data Security
Agent workflows are designed around secure customer data access, protected system boundaries, controlled retrieval, and customer-specific security requirements.
Read Designing a Governed Manufacturing Agent Workflow
Annex 22-Aligned Human-in-the-Loop
Agents gather evidence, explain recommendations, and route decisions to qualified humans. In regulated workflows, agents assist decision-making; humans remain accountable.
Read Annex 22 and AI Agents
The Category
Regulated manufacturers need governed agents, not generic autonomy.
Generic AI agents are not enough for manufacturing environments where decisions affect quality, compliance, uptime, yield, customer commitments, and audit readiness.
Connected Manufacturing Agents are built for practical plant workflows with defined roles, approved data sources, permission-aware access, evidence trails, escalation rules, and human review points.
Connected Manufacturing Agents are built for practical plant workflows with defined roles, approved data sources, permission-aware access, evidence trails, escalation rules, and human review points.
Bounded by workflow
Each agent is designed around a specific manufacturing use case, not an open-ended mandate.
Read Designing a Governed Manufacturing Agent Workflow
Bounded by data access
Agents use secure, role-based access to approved systems and data sources.
Read Designing a Governed Manufacturing Agent Workflow
Bounded by accountability
Agents recommend and escalate. Qualified humans remain responsible for regulated decisions.
Read Annex 22 and AI Agents
Design Partner Program
Join our 90-Day Design Partner Program.
We are inviting a small group of qualified manufacturers to help shape the first generation of Connected Manufacturing Agents.
Design partners work with us on one focused, high-value use case such as quality investigation, root cause analysis, yield loss, downtime, maintenance intelligence, or compliance evidence gathering.
This is not an open-ended AI experiment. It is a 90-day, thin-slice program built around a defined workflow, approved data sources, role-based access, human review checkpoints, and measurable value.
Talk to Us About Fit
Design partners work with us on one focused, high-value use case such as quality investigation, root cause analysis, yield loss, downtime, maintenance intelligence, or compliance evidence gathering.
This is not an open-ended AI experiment. It is a 90-day, thin-slice program built around a defined workflow, approved data sources, role-based access, human review checkpoints, and measurable value.
From Conversational AI to the Agentic Application
Conversational AI answers questions. Agents coordinate governed action.
Conversational AI helps teams ask natural-language questions across manufacturing systems. Agents go further. They monitor signals, investigate related events, gather evidence, recommend next steps, and escalate decisions to qualified people.
For regulated industries, that difference matters. The agent is not just producing an answer. It is helping coordinate a workflow across quality, production, maintenance, engineering, compliance, and management while respecting data access and human review requirements.
For regulated industries, that difference matters. The agent is not just producing an answer. It is helping coordinate a workflow across quality, production, maintenance, engineering, compliance, and management while respecting data access and human review requirements.
Conversational AI
- Ask questions in plain English
- Retrieve data across systems
- Return answers, charts, and summaries
- Reduce reporting and dashboard delays
- Help teams understand what happened
Read Siemens Opcenter and Conversational AI
Governed Agentic Application
- Monitor changing conditions
- Investigate causes across systems
- Gather and preserve evidence
- Respect role-based access controls
- Recommend next-best actions
- Escalate decisions to qualified humans
- Support auditability and review
Read Governed AI in Manufacturing
Secure data. Role-based access. Human-in-the-loop by design.
Closed-Loop Orchestration
Agents work across Design, Execute, Measure, and Improve.
Agents are not a fifth step after Improve. They are the orchestration layer across the closed loop.
They help move work from signal to evidence, from evidence to recommendation, and from recommendation to governed human action.
They help move work from signal to evidence, from evidence to recommendation, and from recommendation to governed human action.
Functional Areas
Start where the business pain is visible.
Connected Manufacturing Agents are designed around practical manufacturing functions, not abstract AI capabilities.
The first generation focuses on areas where data is scattered, investigations are slow, and decisions require evidence.
The first generation focuses on areas where data is scattered, investigations are slow, and decisions require evidence.
Quality
Detect rising defects, summarize nonconformance patterns, gather evidence, and recommend containment or inspection steps.
Read AI Agents for Quality Management
Yield
Identify yield drift, correlate process conditions, compare lines or shifts, and surface likely contributors to loss.
Read AI Agents for Yield Improvement
Maintenance
Connect tooling, maintenance events, downtime, defects, and performance signals to support earlier intervention.
Read AI Agents for Predictive Maintenance
Downtime
Investigate recurring downtime patterns, connect events across systems, and recommend next-best operational follow-up.
Read AI Agents for Downtime Reduction
Root Cause Support
Correlate defects, yield, equipment, supplier, shift, process, and maintenance signals into a structured root-cause hypothesis.
Read AI Root Cause Analysis in Manufacturing
Governed routines
Turn a useful investigation into a governed, repeatable routine.
Connected Manufacturing provides one governed agentic application—not a collection of named digital workers.
Authorized users ask focused manufacturing questions across approved systems and documents. The application returns a source-backed answer with evidence, context, and recommended next checks.
When an analysis is useful, the user can save it as a governed routine, run it again when needed, schedule it, share it with authorized colleagues, and monitor its results through alerts, approvals, and review queues.
The same application can support routines across quality, yield, maintenance, downtime, operations, and root cause analysis.
Example Routine 1
Quality Evidence Review
Purpose
Help a quality team identify rising defect patterns and prepare the evidence needed for human review.
Example question
“What defects increased in the last 24 hours, which lots were affected, and what changed before the increase?”
What the application prepares
- Ranked defect changes by line, product, lot, shift, and time window
- Inspection and nonconformance records
- Related maintenance, process, supplier, and downtime signals
- Missing, stale, or conflicting evidence
- Recommended containment or inspection checks
Save as a routine
The quality engineer can save the successful analysis to run each shift, each day, or when a defined threshold is reached.
Governance model
The routine uses approved data sources and role-based access. A qualified quality owner reviews the evidence and remains responsible for containment, disposition, deviation, or escalation decisions.
Example Routine 2
Cross-System Root Cause Investigation
Purpose
Help a cross-functional team assemble evidence and develop testable root-cause hypotheses.
Example question
“Investigate the defect spike on Line 3 and show what changed across quality, yield, maintenance, downtime, and supplier data.”
What the application prepares
- A timeline of relevant events and changes
- Quality, yield, maintenance, tooling, downtime, and supplier evidence
- Ranked hypotheses with supporting and conflicting evidence
- Open questions and missing records
- Recommended validation steps and responsible functions
Save and share as a routine
The user can save the investigation pattern and share it with authorized quality, operations, maintenance, or engineering colleagues. The routine can then be reused for similar events without recreating the analysis from scratch.
Governance model
The application prepares evidence and recommendations. Qualified people determine the root cause, approve corrective actions, and remain responsible for regulated and operational decisions.
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01
Ask
Ask a bounded manufacturing question.
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02
Answer
Receive a visual, interpretation, and linked supporting evidence.
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03
Save
Save useful work as a governed, repeatable routine.
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04
Run
Execute the routine on demand or on an approved schedule.
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05
Share
Make the routine available to authorized users and roles.
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06
Monitor
Receive results, alerts, exceptions, and approval requests.
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07
Review
Use the output within existing human-owned operational and regulated processes.
Operating principle
Self-service routine creation.
Governed application execution.
Human-owned decisions.
Governance
Governed means secure data, role-based access, and human accountability.
In regulated manufacturing, governance cannot be an afterthought. Connected Manufacturing Agents are designed so agent workflows respect customer data boundaries, enforce role-based access, and keep qualified humans accountable for regulated decisions.
Agents assist the work. They do not silently replace human judgment in regulated workflows.
Agents assist the work. They do not silently replace human judgment in regulated workflows.
Role-based access control
Agents respect user roles, permissions, and data boundaries so people and agents only access information they are authorized to use.
Read Designing a Governed Manufacturing Agent Workflow
Customer data security
Agent workflows are designed around secure customer data access, protected system boundaries, controlled retrieval, and customer-specific security requirements.
Read Designing a Governed Manufacturing Agent Workflow
Annex 22-aligned human-in-the-loop
Agents gather evidence, explain recommendations, and route decisions to qualified people. In regulated workflows, agents assist decision-making; humans remain accountable.
Read Annex 22 and AI Agents
Evidence trail
Agents preserve source evidence, retrieved records, prompt context, recommendation rationale, and review history.
Read Designing a Governed Manufacturing Agent Workflow
Auditability
Workflows are designed so teams can explain what the agent accessed, what it recommended, who reviewed it, and what decision was made.
Read Governed AI in Manufacturing
Performance monitoring
Agent outputs, review patterns, exceptions, escalations, and outcomes should be monitored over time.
Read How to Validate and Monitor Manufacturing Agent Performance
90-Day Design Partner Program
Help shape governed manufacturing agents around a real operating constraint.
We are recruiting design partners for a focused 90-day program.
The program is designed for manufacturers that want to explore governed agents using real workflows, real systems, secure data access, role-based permissions, human review, and measurable business outcomes.
The right first use case is usually narrow and valuable: one recurring defect family, one downtime pattern, one yield issue, one root-cause workflow, or one compliance evidence bottleneck.
The program is designed for manufacturers that want to explore governed agents using real workflows, real systems, secure data access, role-based permissions, human review, and measurable business outcomes.
The right first use case is usually narrow and valuable: one recurring defect family, one downtime pattern, one yield issue, one root-cause workflow, or one compliance evidence bottleneck.
Program structure
Weeks 1–2
Select the constraint
Pick the use case, business owner, user group, source systems, review points, governance requirements, and success criteria.
Read Designing a Governed Manufacturing Agent Workflow
Weeks 3–5
Connect the evidence
Identify and connect the data needed from MES, QMS, PLM, ERP, SCADA, IIoT, maintenance, supplier, or other
relevant systems.
Map role-based access rules, data security requirements, and permitted retrieval paths.
Read Designing a Governed Manufacturing Agent Workflow
relevant systems.
Map role-based access rules, data security requirements, and permitted retrieval paths.
Weeks 6–8
Configure the Governed Application and Routine Controls
Define the agent’s role, prompts, retrieval paths, recommendation logic, escalation rules, human review checkpoints, and evidence trail.
Read Designing a Governed Manufacturing Agent Workflow
Weeks 9–12
Validate, launch, and measure
Test against known cases, compare outputs with expert review, train users, monitor performance, and measure value.
Read How to Validate and Monitor Manufacturing Agent Performance
Who should apply
Good fit
- Regulated or quality-sensitive manufacturer
- Clear operating pain in quality, yield, maintenance, downtime, root cause, or compliance evidence
- Access to relevant system data
- Business owner willing to participate
- Need for governed AI, not uncontrolled automation
- Ability to support a 90-day pilot
- Willingness to define human review and accountability
Not the right fit yet
- No clear use case
- No access to source system data
- Looking for fully autonomous decision-making
- No internal owner for review and adoption
- Not ready to evaluate value within 90 days
- No ability to define access permissions or review roles
Design Partner Program
Apply for the 90-Day Design Partner Program
Thank you for your interest in the Connected Manufacturing 90-Day Design Partner Program.
We will review your use case, systems, and governance requirements and follow up if there is a strong fit.
Recommended hidden fields: Source page, CTA clicked, UTM source, UTM medium, UTM campaign, UTM content, Form submission date, Design Partner Program interest = true, Agents launch = true.
Ready to explore governed agents for your manufacturing workflow?
Join our 90-Day Design Partner Program and help shape practical, secure, human-supervised agents for regulated manufacturing operations.