Domain Twin™ × NemoClaw Control Platform

NPI Twin™

From NPI risk to production decisions,unifying data, simulation, agents, and governance in one control platform.

NPI Twin™ is powered by Domain Twin™ and works with NemoClaw to coordinate agents, bringing data, simulation, rules, and evidence into one NPI decision loop.

Reserve a DemoSee a Day in NPI
Control Architecture

Unify data, simulation, agents, and governance in one control platform

Three layers: data enters, Domain Twin™ controls, and NPI Twin™ executes. NemoClaw coordinates agents.

1

Data & Systems

Connect engineering, manufacturing, quality, and supply chain data.

CAD / BOMPLM / ALMMES / ERPQuality / Test
→
2

Domain Twin™ Control Platform

Govern knowledge, simulation, agents, rules, and evidence.

Data ContextSimulationGovernanceAudit
→
3

NPI Twin™ Field Action

Turn control capabilities into risk decisions, reviews, and execution.

Risk DecisionsReview PackAction Tracking

Five-Layer Control Reference Architecture

GPU · NVIDIA AI · NVIDIA NemoClaw · Domain Twin · NPI Twin
5
4
3
2
1

NPI Twin™ Ready-to-Go Agent

Prebuilt NPI workflows for risk prediction, simulation, and review packs.

Risk PredictionSimulationReview Pack

Domain Twin™ Platform

Connects manufacturing data, know-how, models, and workflows into a reusable control layer.

DataKnow-howModelsWorkflows

NVIDIA NemoClaw Runtime Layer

Adds runtime security and policy guardrails for controlled agent execution.

Runtime SecurityPolicy GuardrailsControlled Execution

AI Capability Layer

Provides model serving, customization, reasoning, and simulation services.

NVIDIA NIM™NVIDIA NeMo™NVIDIA Omniverse™

GPU Infrastructure Layer

Provides compute and deployment for real-time NPI agent workloads.

GPUDGXHGXSecure Deployment
Not Just Answers. Executable Action.

NPI Twin™ is not a single assistant. It is an executable workflow.

Assistant agents help teams understand. NemoClaw coordinates multiple agents to move work toward outcomes.

Assistant Agent

Support Point Decisions

  • Understand Engineering Intent
  • Summarize Pilot Runs and Anomalies
  • Explain Model Results
  • Prepare Review Materials
vs
NemoClaw Execution Layer

Coordinate the Full NPI Workflow

  • Connect Factory Data and Tools
  • Risk Ranking & Task Assignment
  • Trigger Prediction, Simulation & Action Cards
  • Track Status and Continue Monitoring
A Day in the Life of an NPI Engineer

From Risk Review to Continuous Monitoring

Follow a day in the life of an NPI engineer and see how Domain Twin™ turns data, simulation, and agents into an executable NPI workflow.

Daily FlowSelect a time to view each stage
NPI Twin Control Console
Live
09:00

Risk Review

Prioritize today’s NPI risks.

01EngineerWhich risks should be handled first today?
→
02Domain Twin™Integrate MES, SPC, AOI, ET, and QMS.
→
03NPI AgentRank risks and prepare next actions.
Factory SystemsWriteback & Monitoring
GovernanceRules & Evidence Trail
Runtime SecurityNemoClaw policy guardrails
OutputRisk list, task recommendations, and owners.
09:00
Workflow Step

Risk Review

Prioritize today’s NPI risks.

Engineering Intent

Which risks should be handled first today?

Control Platform

Integrate MES, SPC, AOI, ET, and QMS.

Agent Action

NemoClaw coordinates monitoring agents and ranks the top three risks.

OutputRisk list, task recommendations, and owners.
Current StageRisk Review
Workflow StatusRisks Ranked
Risk RankingTask AssignmentEvidence Trail
Control Loop Simulation

From Parameter Drift to Approved NPI Action

See how Domain Twin™ connects monitoring, analysis, action, and approval into one governed loop.

Real-Time Parameter Monitoring

Agentic Parameter Control Loop

The lead agent assigns tasks, the monitoring agent checks parameters, and the analysis agent explains causes and prepares recommendations.

Process Drift Index
58
Recipe Parameter183°C
Risk Score62
Agent StatusReview
Action Card + Review Pack

Recommendation Generated

As agents monitor, analyze, recommend, approve, and execute, the review pack updates in sync.

1
Parameter Monitoring LoopThe monitoring agent checks equipment and recipe parameters and flags early drift.
2
Root Cause AnalysisThe analysis agent identifies recipe temperature as the main drift factor.
3
Action CardAdjust recipe parameters before the next batch.
4
Human Approval + ExecutionThe decision owner reviews the action card. After approval, the lead agent updates the recipe and continues monitoring.
Decision SummaryParameter drift is visible but still controllable. NPI Twin™ recommends review and prepares the evidence trail before execution.
Control Concept Highlights

Bring data, simulation, NemoClaw, and governance into one NPI loop

Domain Twin™ brings data sources, simulation logic, NemoClaw coordination, governance rules, and evidence trails into one control platform.

Controlled · Governed · Auditable
A

See Risk Earlier

Connect pilot, quality, process, and historical case data to identify risk earlier.

  • Risk Prioritization
  • What-If Scenario Validation
  • Evidence Before Decisions
B

Unify Data, Workflows & Agents

Bring engineering, manufacturing, quality, and supply chain data into one control platform so Domain Twin™ and NemoClaw work from the same context.

  • Multi-Source Data Connection
  • Agent Coordination
  • Shared Cross-Team Context
C

Built-In Governance and Traceable Execution

Every recommendation links back to rules, permissions, evidence, and audit records.

  • Policies & Rules
  • Audit & Traceability
  • Standardize Knowledge Reuse
LIVE DEMO

SEE NPI TWIN LIVE AT COMPUTEX 2026

See how Domain Twin™ turns data, simulation, and agents into an executable NPI workflow.

BoothR0113
VenueTaiNEX 2, 4F
Reserve a Demo