A retail chain sourcing from 800+ vendors experienced 15% of shipments arriving late, with an average delay of 4.2 days. Vendor selection was based on historical relationships rather than performance data. Quality issues with inbound goods caused $6M in annual returns and write-offs.

Purchase order creation was manual, taking 2-3 days from requisition to submission. Shipment tracking required checking multiple carrier portals, and delays were discovered only when goods failed to arrive. No systematic vendor performance scoring existed, making it impossible to identify and address underperforming suppliers.

The retailer needed automated vendor evaluation, procurement, and real-time supply chain visibility.

The Solution

Agents that score vendors, automate procurement, track shipments, and inspect quality

Vijan.AI deployed 5 agents across the supply chain. The Supplier Scorer continuously evaluates all 800 vendors on quality metrics, lead time reliability, cost competitiveness, and responsiveness. The PO agent automates purchase order creation, routing, and submission based on demand signals and optimal vendor selection. The Shipment Tracker monitors all inbound shipments via carrier APIs, predicting delays before they impact operations. The Quality Inspector manages sampling protocols and tracks defect rates by vendor and SKU. The Exception agent escalates critical delays and activates backup suppliers when primary vendors underperform.

Autonomous Agents

How each agent reasons, decides, and acts

Step 1 · Vendor Ops

Vendor Management Agent

Vendor Performance Management

Scores vendors on quality, delivery, and cost to optimize supplier selection and contract terms.

Input

Vendor performance data, delivery times, quality metrics, pricing

Output

Vendor scorecards with recommendations

Calls vendor scoring tool to rank suppliers by on-time delivery, defect rates, and cost competitiveness
Calls contract management tool to track terms, renewals, and renegotiation opportunities
Autonomous decision: recommend preferred vendors, flag underperformers for replacement
Routes vendor insights to procurement and Inventory Valuation agent

Step 2 · Valuation

Inventory Valuation Agent

Inventory Valuation and Accounting

Calculates inventory value using FIFO/LIFO methods, tracks write-downs, and ensures accounting accuracy.

Input

Inventory levels, purchase prices, sales data, accounting policies

Output

Inventory valuation with GL postings

Calls FIFO/LIFO calculation tool to value inventory per accounting standards
Calls write-down tracking tool to identify obsolete or damaged goods for markdown
Autonomous decision: trigger markdowns for slow-moving inventory, adjust reserves for shrinkage
Routes valuation data to Shrinkage Detector and financial reporting

Step 3 · Loss Prevention

Shrinkage Detection Agent

Shrinkage and Theft Detection

Identifies inventory shrinkage from theft, damage, or errors using predictive analytics and pattern recognition.

Input

Inventory counts, POS data, surveillance alerts, transaction logs

Output

Shrinkage reports with root cause analysis

Calls loss detection tool to compare physical inventory vs system records
Calls theft pattern analysis tool to identify high-risk products, locations, and time periods
Autonomous decision: trigger security alerts, recommend anti-theft measures (locks, cameras)
Routes shrinkage data to Perishables Agent and store operations for mitigation

Step 4 · Perishables

Perishable Goods Agent

Perishable Goods Optimization

Monitors expiration dates, triggers markdowns, and optimizes replenishment to minimize waste.

Input

Perishable inventory, expiration dates, sales velocity, temperature logs

Output

Markdown triggers and replenishment plans

Calls expiry monitoring tool to track shelf life and flag near-expiration items
Calls markdown trigger to automate price reductions before spoilage
Autonomous decision: prioritize near-expiry items in promotions, adjust order quantities
Routes perishables data to Store Layout agent for optimal placement

Step 5 · Merchandising

Store Layout Agent

Store Layout and Planogram Optimization

Analyzes customer traffic patterns and optimizes product placement to maximize sales and customer experience.

Input

Traffic heatmaps, sales by location, planogram compliance, seasonal trends

Output

Optimized planograms with placement recommendations

Calls heatmap analysis tool to identify high-traffic zones and dead spots
Calls planogram generation tool to design optimal shelf layouts per category
Autonomous decision: place high-margin items at eye level, position impulse buys near checkout
Routes planograms to store operations for execution and compliance tracking

Results

Measurable impact within 90 days of deployment

30%

Faster Delivery

Average delivery time reduced by 30% through optimized vendor selection and proactive delay management.

Late Shipment Rate

Late shipments reduced from 15% to 4%. Predictive delay detection enables mitigation 3 days before impact.

$8M

Quality Savings

Returns and write-offs from quality issues reduced from $6M to $1.8M through vendor scoring and inspection.

85%

PO Automation

85% of purchase orders created and submitted automatically. Procurement cycle reduced from 3 days to 4 hours.

Implementation

From pilot to production in 12 weeks

Week 1-4

Agent Design & Tool Integration

Defined agent capabilities, connected ML model, rules engine, graph DB, and chargeback API tools. Configured orchestrator routing logic.

Week 5-8

Shadow Mode & Autonomous Tuning

Agents ran in shadow mode on 10% of transactions. Tuned decision thresholds, tool call parameters, and feedback loop retraining frequency.

Week 9-12

Full Autonomous Deployment

Production rollout across all channels. Agents operating fully autonomously with human-in-the-loop for critical escalations only.

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