Executive Summary
Global manufacturing enterprises operate across complex, multi-plant and multi-supplier ecosystems where traceability is critical for regulatory compliance, product quality, and recall preparedness. Traditional track and trace systems struggle with fragmented data, manual processes, and limited visibility across internal production and external supply chain networks.
Nexastack delivers an Agentic AI–powered Track & Trace platform that enables end-to-end visibility across inside-plant and outside-plant operations. Built on private cloud AI and sovereign AI infrastructure, Nexastack orchestrates specialized AI agents to automatically capture events, maintain tamper-proof genealogy, and execute recall workflows with enterprise-grade security and observability.
By combining real-time data ingestion, AI-driven lineage analysis, and autonomous workflow orchestration, manufacturers achieve audit-ready traceability, faster recall execution, and continuous quality improvement—without compromising data sovereignty or operational control.
Business Problem: Why Track & Trace Breaks at Scale
Inside Plant Challenges
-
Manual or inconsistent capture of batch, lot, and transformation events
-
Disconnected MES, SCADA, and quality systems
-
Limited visibility into rework, scrap, and non-conformance events
Outside Plant Challenges
-
Incomplete or delayed supplier and logistics data
-
Inconsistent lot and serial formats across partners
-
Lack of end-to-end chain-of-custody visibility
Compliance & Recall Risks
-
Slow root-cause investigations
-
High effort to prepare audit documentation
-
Delayed or incomplete recall execution increases regulatory and brand risk
Business Goals
-
Achieve complete traceability from raw material intake to final shipment
-
Enable rapid recall readiness with precise impact identification
-
Improve product quality and supplier accountability
-
Reduce manual effort and data errors through automation
-
Ensure compliance in regulated and sovereign data environments
What End-to-End Track & Trace Means
-
Track – Forward visibility into where products, batches, and shipments move
-
Trace – Backward visibility into material origin, suppliers, and production history
-
Genealogy – Parent-child relationships showing how components transform into finished goods
Nexastack unifies all three across inside and outside plant operations.
Solution Overview: Nexastack Agentic Track & Trace
Nexastack provides a context-first, agentic infrastructure for enterprise traceability.
Core Capabilities
-
Automatic registration of lot, batch, serial, and transformation events
-
Unified traceability records across plants, suppliers, and logistics partners
-
Real-time monitoring, alerts, and recall triggers
-
Audit-ready dashboards and compliance reporting
Secure by Design
-
Private cloud AI deployment for sensitive manufacturing data
-
Sovereign AI controls for data residency, access, and governance
-
Tamper-evident execution logs and policy-based workflows
High-Level Architecture
Data Sources → Event Normalization → Genealogy Graph → AI Agents → Orchestrated Workflows → Dashboards & APIs
-
Inside Plant: IoT sensors, MES, SCADA, quality systems
-
Outside Plant: Supplier systems, WMS, TMS, logistics milestones
-
Agentic Layer: Autonomous agents validate data, analyze lineage, and trigger actions
-
Deployment: On-prem, edge, or private cloud AI with centralized governance
Recommended AI Agents
-
Track Agent: Captures movement and transformation events in real time
-
Trace Agent: Maintains genealogy and performs recall impact analysis
-
Data Quality Agent: Ensures completeness, consistency, and integrity of trace data
Key Workflows Powered by Agentic AI
1. Inside Plant Traceability
-
Automated batch and lot registration
-
Real-time capture of production, rework, and quality events
-
Continuous validation of process data
2. Outside Plant Traceability
-
Supplier lot ingestion and verification
-
Shipment and logistics milestone tracking
-
Unified visibility across partners
3. Recall Readiness Workflow
Input: Finished product serial or batch
Output:
-
Upstream components and supplier lots
-
Impacted production runs and shipments
-
Automated containment and notification actions
-
Audit-ready recall report
Example Scenario: Rapid Recall Investigation
A quality issue is detected in a finished product batch. Using Nexastack, the organization traces the product back through its entire production and supplier history in seconds. The system identifies affected lots, production lines, and shipped destinations, automatically triggering containment workflows and generating compliance documentation—significantly reducing response time and risk.
Results & Benefits
Business Impact
-
Reduce time-to-trace from hours or days to minutes
-
Improve recall containment speed by 50–80%
-
Cut audit preparation effort by 30–60%
-
Enhance product quality and supplier accountability
Technical Impact
-
Scalable architecture across global plants and suppliers
-
Real-time analytics for proactive issue detection
-
Secure, compliant traceability using sovereign AI
Built for Regulated and Global Enterprises
-
Data residency and access controls across regions (US, EU, GCC, APAC)
-
Tamper-proof logs and signed execution for chain-of-custody
-
Alignment with industry regulations across pharma, food, automotive, and electronics
Conclusion
Track & Trace with Agentic AI fundamentally transforms how manufacturers manage compliance, quality, and recall readiness. By combining AI agents, agentic orchestration, and private cloud AI infrastructure, Nexastack delivers secure, scalable, and audit-ready traceability across inside and outside plant operations—enabling enterprises to operate with confidence, transparency, and control.
Frequently Asked Questions (FAQs)
Advanced FAQs on Track & Trace using Agentic AI on private cloud infrastructure.
How does Agentic AI enhance track & trace in complex supply chains?
By autonomously correlating events, detecting anomalies, and resolving gaps across logistics, production, and distribution data.
Why deploy track & trace systems on a private cloud?
To ensure data sovereignty, low-latency processing, and compliance with industry and regional regulations.
How do AI agents maintain traceability accuracy at scale?
By continuously validating data lineage, reconciling signals, and adapting to real-time process changes.
Which industries benefit most from agentic track & trace?
Manufacturing, pharmaceuticals, food & beverage, and regulated logistics networks.
