How an Agentic ELT Accelerator Transforms Supply Chain Analytics End-to-End?

Built for modern Supply chain analytics and Operations teams, the Supply Chain Insights Accelerator enables end-to-end visibility across Purchase Orders, Shipments, Inventory, Warehousing, Logistics Events, Supplier Feeds, and Fulfillment pipelines powered by LLM-driven Agentic ELT automation.

Dataplatr’s Agentic ELT (AELT) framework introduces AI-first automation into supply chain analytics by ingesting, validating, and operationalizing multi-source supply chain data on the Databricks Lakehouse. Using LLM-based data agents with human-in-the-loop validation, the accelerator applies deep supply-chain domain intelligence to create a unified Supply Chain Control Hub driving inventory visibility, supplier performance insights, logistics tracking, and fulfillment analytics.

With AELT for Supply Chain, teams benefit from intelligent metadata enrichment, automated schema alignment, event-to-event stitching (PO → Shipment → Receipt → Fulfillment), incremental pipeline generation, and conversational SQL. This reduces manual engineering effort by up to 60% while ensuring complete transparency, traceability, and governance across the entire supply chain lifecycle.

Key Supply Chain Data & Operational Challenges

Supply chain organizations commonly face two critical challenges:

1. Fragmented Data & Complex Integrations - Purchase orders, shipments, ASNs, warehouse events, and carrier updates reside in disparate, high-volume systems. Consolidating these datasets into a unified, end-to-end order-to-delivery view is complex, time-consuming, and error-prone.

2. Operational Silos Across Functions - Procurement, logistics, warehousing, and finance often operate independently, limiting visibility into delays, supplier reliability, inventory risks, and fulfillment bottlenecks.

Agentic ELT Architecture for Supply Chain Analytics

1. Bronze (L0) - Raw ingestion of supply chain datasets from ERP, WMS, TMS, and logistics systems.
2. Silver (L1–L2) - AI agents automatically generate standardized SQL, apply incremental loading logic, and validate primary keys using Databricks Delta Live Tables (DLT).
3. Gold (L3) - A conversational agent helps users define business-ready analytics tables such as On-Hand Inventory using natural language. The agent validates, deploys, and governs DLT SQL automatically.

End-to-End Agentic ELT Pipeline Flow

1. Metadata Enricher Agent (Bronze) - Automatically generates semantic metadata for POs, shipments, ASNs, receipts, inventory movements, and carrier events with HITL validation.
2. Silver SQL Generator Agent - Creates standardized L1 views with consistent schemas and validated transformation logic.
3. Conversational Gold Agent - Enables supply chain teams to build advanced analytics tables simply by describing requirements (e.g., “Create a PO-to-Delivery cycle time summary”). The agent validates logic, resolves SQL errors, and enforces KPI consistency.
4. DLT Execution - A single Delta Live Tables pipeline constructs the complete supply chain lifecycle stitching POs → Shipments → Receipts → Deliveries with built-in lineage, CDC handling, data quality checks, and auditability.

Supply Chain Hub Functional Insights (Gold Layer)

Once the agentic pipeline is deployed, the Transaction Analytics Accelerator delivers ready-to-use insights:

1. End-to-End Order & Shipment Visibility - Provides complete traceability from Purchase Order → Supplier Dispatch → Shipment → Warehouse Receipt → Customer Delivery. 
   Automatically stitches multi-system events (ERP, WMS, TMS) to create a unified, timeline-ready supply chain analytics journey.

2. Supplier & Fulfillment Performance Intelligence - Tracks supplier behaviour across On-Time Delivery, Fill Rate, Lead Time Variance, ASN accuracy, and quality issues. 
   Integrates carrier and warehouse data to offer a holistic view of fulfilment performance and bottlenecks.

3. Operational Logistics Performance Monitoring - Delivers core supply chain KPIs including OTIF, cycle times, inventory ageing, order backlog, and dock-to-stock duration.

Provides lane-level, route-level, and warehouse-level insights to optimize capacity, efficiency, and service performance.

Pre-Built Supply Chain Dashboard Widgets

Supply Chain Operations

1. Inbound & Outbound Volume Trends – Daily and weekly shipment patterns to identify peak demand and capacity needs
2. Order Cycle Time Trend – Tracks time from PO creation to delivery, highlighting delays across functions
3. OTIF Performance – Visualizes reliability across suppliers, carriers, and routes
4. Exception & Delay Monitoring – Surfaces delays, shortages, and disruptions impacting service levels

On-Hand Inventory

1. Inventory Position Summary – Summarises on-hand, allocated, available-to-promise (ATP), and safety stock levels across warehouses and DCs.
2. Stock Aging Trend – Tracks aging buckets to surface slow-moving, non-moving, and excess inventory at SKU, category, and warehouse levels.
3. Reorder & Stockout Risk – Highlights items nearing reorder points, potential stockouts, and high-demand SKUs requiring urgent replenishment.
4. Top/Bottom Inventory Performers – Identifies high-velocity vs. low-velocity SKUs based on turnover rate, demand variability, and stock utilization.

Key Capabilities of the Agentic ELT Supply chain analytics Accelerator

1. Auto-generates standardized descriptions for orders, shipments, inventory events, and fulfillment milestones.
2. AI-driven reconstruction of end-to-end supply-chain journeys Order → Pick → Pack → Ship → Deliver → Return.
3. Produces DLT-ready SQL for Order Hub, Inventory Snapshot, Fulfillment Performance, and Logistics Tracking tables.
4. Supports conversational (chat-based) creation of Gold-level KPIs like OTIF, Fill Rate, Lead Time, and Service Level.
5. Automatically detects and fixes SQL logic issues, schema drift, and broken supply-chain transformations.
6. Provides CDC-based near-real-time updates on order status, inventory position, and shipment movement.

Marketplace Deliverables

1. Production-Ready Notebooks: End-to-end AELT pipeline notebooks for Bronze (Ingestion), Silver (Transformation), and Gold (Analytics) with agent-assisted automation.
2. Config Templates: JSON mappings for Supply Chain objects with AI-assisted metadata generation.
3. DLT SQL Files: Automatically generated and validated SQL for incremental tables and Supply chain views
4. CDC & Data Quality Frameworks: Out-of-the-box components for real-time ingestion and data validation.
5. Documentation & Implementation Guide: Step-by-step Databricks setup, object mapping, and AELT deployment manual.

Why Choose Dataplatr’s Supply chain analytics Hub Agentic ELT Accelerator

1. Agentic Automation – Eliminates manual stitching logic and complex SQL
2. Faster Time-to-Value – Dashboards ready in hours, not weeks
3. Deep Supply Chain Domain Expertise – Prebuilt metrics for OTIF, Fill Rate, Cycle Time, Inventory Turns, and Aging
4. Enterprise-Grade Governance – End-to-end lineage, quality checks, and auditability via Unity Catalog
5. Databricks-Native – Built on Delta Live Tables and the Lakehouse architecture
6. Scalable & Extensible – Integrates seamlessly with ERP, WMS, and logistics platforms

Transform Supply Chain Analytics with Agentic ELT

Deliver unified inventory, procurement, and logistics insights with AI-powered operational intelligence fully automated on Databricks. 
For a demo or hands-on notebook, feel free to reach out.

Contact us at: [email protected]  
For consultations or custom inquiries: https://dataplatr.com/contact-us 
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