⬡ Supply Chain Dashboard
Real-time operational overview — powered by Vertex AI on Google Cloud · Project: optichain-ai
Inventory Value
$1.2M
▲ +2.5% vs last week
On-Time Shipments
98.2%
▼ −0.2% vs target
Active Stockouts
12
+3 since last week
Forecast Accuracy
92.1%
▲ +1.5% vs last month
🔴 Critical: Cascading Supply Risk Detected
Vertex AI agents have identified a systemic risk: Component X-123 supplier (Global Metals Inc.) shows 23% delivery degradation correlated with Steel Beam demand spike (+18% MoM). This cross-pillar dependency will breach Q3 procurement SLA within 14 days if unaddressed.
✅ Prescriptive Action: Reallocate $45K procurement budget to Reliable Resources Ltd. (backup supplier) and pre-order 2,400 units at $18.50/unit to avoid estimated $88K stockout cost impact.
📈 Sales Overview
Actual vs. Forecasted Sales
Live
Actual
Forecast
🏭 Supplier Performance
On-time delivery & quality scores
| Supplier | On-Time | Quality | Risk |
|---|---|---|---|
| Global Metals | 77% | 91% | High |
| Reliable Res. | 97% | 99% | Low |
| Component Sol. | 94% | 96% | Low |
| Pacific Supply | 82% | 88% | Med |
💰 Cost & Financial Insights
Carrying, procurement & stockout
Total Carrying Cost$125,430
Procurement Spend (QTD)$1.8M
Stockout Cost Impact$88,200
Cost Savings Achieved$45,000
Cost Per Order$12.50
Inventory / Working Cap.22%
🔗 Live Supply Chain Flow — End-to-End Visibility
Streaming from BigQuery
Suppliers
4 Active
OK
→
Inbound Logistics
D+2.3
Delay
→
Receiving (WH)
98.2%
OK
→
Stage Tables
Syncing
D365
→
BigQuery DW
Live
GCP
→
Inventory
12 Outs
Alert
→
Fulfillment
4,200/day
OK
→
Customer
98.2% OT
OTIF
⚙️ Operational KPIs
Order Fill Rate96.4%
Inventory Turnover8.2x
Days of Supply23 days
Perfect Order Rate94.1%
Supplier Lead Time (avg)7.3 days
Demand Forecast MAPE7.9%
☁️ GCP Native Architecture
optichain-ai
1
Dynamics 365 ERP Connector
Azure API → Cloud Pub/Sub → Stage Tables
2
Dataflow ETL Processing
Apache Beam · Post-processing pipeline
3
BigQuery Data Warehouse
Staging → Processed → Analytics layer
4
Vertex AI Agents
Demand · Procurement · Inventory models
5
GKE Kubernetes Cluster
optichain-ai · us-central1 · 6 nodes
📡 Real-Time Demand Sensing
AI agents continuously analyze sales data, trends, economic indicators, and seasonal patterns · Vertex AI Forecasting · 92.1% accuracy
Forecast Accuracy
92.1%
SKUs Monitored
5
Alerts Active
2
Horizon
8 weeks
Last sync: loading...
92.1%
📊 Live Demand Forecast — Vertex AI ✓
📡
Loading demand forecast from Vertex AI...
📈 All SKU Trend Summary
⚡ Demand Alerts
🤖 Autonomous Procurement Agent
AI detects supply disruptions, scores suppliers, raises POs, and sends email approvals — 24/7 without human initiation
Auto Orders (Month)
23
▲ +4 vs last month
Cost Savings
$45K
▲ This quarter
Pending Approval
3
Awaiting your action
Avg Lead Time
6.2d
▼ -1.1d vs target
🔔 AI Procurement Alerts — Action Required
CRITICAL
⚠ Steel Beam Stockout Risk
2h ago
AI Recommended
4.2d
Days Supply
9,944
Units On Hand
77%
SUP001 OTD Rate
97%
SUP002 OTD Rate
SKU-BEAM-001 is at 4.2 days supply — below the 7-day safety threshold. Primary supplier SUP001 delivery rate has dropped to 77%. AI recommends an emergency PO from Reliable Resources (SUP002) who has 97% on-time delivery and available stock.
📋
PO-2891 — Reliable Resources Ltd (SUP002)
SKU-BEAM-001
· 2,400 units
· Lead time: 5 days
$44,400
HIGH
📈 Copper Wire Forward Contract
4h ago
Market Signal
+12%
LME Price Forecast
6 wks
Window
$8,200
Potential Saving
LME copper futures are signalling a 12% price increase within 6 weeks. Locking in a forward contract at current spot pricing saves an estimated $8,200 versus procuring at market rate after the surge.
💵
PO-2892 — SemiconductorWorks Taiwan (SUP005)
ARM Cortex-M7 512KB
· Forward contract
· 90-day lock-in
$18,200
MEDIUM
📦 Microchip Safety Stock Top-Up
6h ago
Demand Forecast
+11%
Demand Increase
400
Units to Add
6 wks
Forecast Horizon
Demand forecast is trending +11% over the next 6 weeks. Current safety stock buffer will be insufficient by week 4. Component Solutions (SUP003) has confirmed available capacity and can fulfil within the lead time window.
📋
PO-2893 — ChemReagents GmbH (SUP003)
Phosphate Buffer Saline 1L
· 400 units
· Lead time: 8 days
$9,600
📋 Recent PO Activity — D365 OData
| PO | SUPPLIER | SKU | VALUE | STATUS |
|---|---|---|---|---|
| PO-2891 | Reliable Resources | SKU-BEAM-001 | $44,400 | PENDING |
| PO-2892 | Pacific Supply | SKU-CABLE-4AWG | $18,200 | PENDING |
| PO-2893 | Component Solutions | SKU-PUMP-CENT | $9,600 | PENDING |
| PO-2877 | Global Metals | SKU-BEAM-001 | $38,800 | APPROVED |
| PO-2865 | Pacific Supply | SKU-CABLE-4AWG | $22,500 | DELIVERED |
🏆 Supplier Scoreboard — D365 VendorV2
📦 Dynamic Inventory Optimization
Real-time reorder intelligence — D365 InventoryOnHandV2 · AI-adjusted safety stock · Lead time risk scoring
Total Inventory Value
$915K
Critical Stockouts
2
VALVE + PUMP
Below Reorder
3
Healthy SKUs
2
Avg Days Supply
11.0d
📊 Inventory Status — D365 InventoryOnHandV2
| SKU / PRODUCT | ON HAND | REORDER PT | DAYS SUPPLY | LEAD TIME | STATUS | VALUE | ACTION |
|---|
📉 Inventory Level Visualization
💡 AI Reorder Recommendations
🔄 Data Pipeline & Integration
Multi-source ingestion · D365 · Odoo · QAD · SAP · Servigistics · GCP Data Lake · Vertex AI · Looker · Power BI
✓ All Pipelines Healthy
GCP us-central1 · optichain-ai
Records / Day
2.4M
All sources combined
Servigistics Sync
1,240 SKUs
Nightly · 02:00 UTC
Failure Signals Sent
247 YTD
OptiChain → Servigistics
Demand Accuracy
94.2%
With OC feedback loop
⚠️ Systemic Risk Indicators
Proactive risk identification — cross-pillar operational drag, macro-budget inefficiencies · Vertex AI scoring every 5 minutes
🔴 Critical & High Risk EventsLive
📊 Risk Score Trend — Last 30 Days
🏭 Supplier Risk
📦 Inventory Risk
🚚 Logistics Risk
🕸 Cross-Pillar Cyclical Correlation
Breaking data silos — hidden correlations across Procurement, Inventory, Demand, Finance · Updated from BigQuery every hour
📊 Pillar Correlation Matrix
⚡ Top Correlations — Live Signals
📈 Cross-Pillar Impact Timeline — Last 12 Months
💰 ROI & Run-Rate Forecasting
Budget-language reporting: OpEx forecasts, cost avoidance, headcount efficiency, risk premiums · Vertex AI forecast engine
📊 Budget vs Actual Run Rate — FY2024
💹 Sales Forecast vs Actual — Units
🎯 Cost Avoidance Breakdown
📈 12-Month ROI Projection (Vertex AI)
☁️ GCP Infrastructure — optichain-ai
Google Kubernetes Engine + Vertex AI + BigQuery · us-central1 · All processing stays within Google Ecosystem
GKE Cluster Health
100%
6/6 nodes healthy
Vertex AI Models
5
All models deployed
BigQuery Slots
2,000
Flat-rate commitment
Monthly GCP Spend
$8.4K
↓ −12% vs last month
⚙️ GKE Kubernetes Cluster
Healthy
optichain-cluster · us-central1-a · GKE Autopilot
| Service | Replicas | CPU | Memory | Status |
|---|---|---|---|---|
| demand-sensing-agent | 3/3 | 45% | 62% | Running |
| procurement-agent | 2/2 | 32% | 48% | Running |
| inventory-optimizer | 2/2 | 28% | 41% | Running |
| d365-connector | 2/2 | 18% | 29% | Running |
| bq-dataflow-pipeline | 4/4 | 67% | 74% | Running |
| optichain-api | 3/3 | 22% | 35% | Running |
🤖 Vertex AI Models — optichain-ai
1
demand-forecast-v3
AutoML Forecasting · MAPE 7.9% · 14 features
2
supplier-risk-classifier
Custom Tabular · AUC 0.94 · 28 features
3
eoq-optimizer-agent
Reinforcement Learning · Optimization model
4
anomaly-detector
Isolation Forest · Real-time scoring
5
procurement-nlp-agent
Gemini 1.5 Pro · Negotiation & PO drafting
Vertex AI
BigQuery ML
GKE
Pub/Sub
🔗 Dynamics 365 Integration
Real-time sync with D365 Finance & Operations — OData REST → Cloud Pub/Sub → BigQuery → OptiChain AI
D365 Connection
● LIVE
Last OData Sync
—
Records Synced
47,284
Sync Lag
4.2s
API Health
99.8%
📡 D365 OData Entities — Live Sync
SalesOrderHeaderV2
Sales orders + header data
12 recordsActive
SalesOrderLineV2
Order line items + quantities
38 linesActive
InventoryOnHandV2
Real-time inventory positions
8 SKUsActive
VendorV2
Supplier master + contact data
5 vendorsActive
PurchaseOrderHeaderV2
Open POs + approval status
5 POsActive
GeneralJournalEntry
Financial transactions + budgets
280 entriesActive
CustomerV3
Customer master + credit limits
12 accountsActive
ProductsV2
Product catalog + pricing
8 productsActive
🔄 Data Pipeline: D365 → BigQuery
1
D365 OData API
Change tracking · Delta sync · 5-min interval
2
Cloud Pub/Sub
Event streaming · Schema validation · Dead letter
3
Dataflow ETL
Transform + deduplicate · Exactly-once semantics
4
BigQuery DW
supply_chain dataset · Partitioned by date
5
Vertex AI Inference
Demand forecast · Risk scoring · Anomaly detect
6
OptiChain Dashboard
REST API · 30s cache · Live KPI refresh
📊 Sample BigQuery Queries (supply_chain dataset)
-- Open at-risk orders
SELECT order_id, customer,
ai_risk_score
FROM sales_orders
WHERE status='OPEN'
AND ai_risk_score < 50
ORDER BY ai_risk_score ASC
SELECT order_id, customer,
ai_risk_score
FROM sales_orders
WHERE status='OPEN'
AND ai_risk_score < 50
ORDER BY ai_risk_score ASC
-- Inventory below reorder
SELECT sku, product_name,
available_qty, reorder_point,
days_of_supply
FROM inventory_onhand
WHERE available_qty
< reorder_point
SELECT sku, product_name,
available_qty, reorder_point,
days_of_supply
FROM inventory_onhand
WHERE available_qty
< reorder_point
-- Supplier performance
SELECT vendor_id, name,
on_time_rate, risk_score
FROM supplier_performance
WHERE snapshot_date
= CURRENT_DATE()
ORDER BY risk_score ASC
SELECT vendor_id, name,
on_time_rate, risk_score
FROM supplier_performance
WHERE snapshot_date
= CURRENT_DATE()
ORDER BY risk_score ASC
🏭 PTC Servigistics × OptiChain AI
Bidirectional integration demo · Servigistics plans → OptiChain executes → feedback improves the plan · GCP · optichain_ai dataset
✓ Live Integration
6 Bidirectional Tables
📊 AGCO PoC Ready
PARTNERSHIP PROPOSITION
Presented to PTC Servigistics · L&T Technology Services / Intelliswift
↓ Servigistics (PTC) Plans
METRIC/VARI-METRIC optimization computes optimal stock targets across every echelon. Weekly cycle. Publishes safety stock, reorder points, ABC/XYZ classification, and demand forecasts.
⇄
API
Bridge
Bridge
⚡ OptiChain AI (LTTS) Executes
Reads Servigistics targets → monitors actual stock live → when IoT flags failure risk, pre-stages parts before Servigistics knows demand exists. Sends richer consumption signals back to improve the Croston model.
"Servigistics tells you what to stock. OptiChain AI makes sure the right part is at the right place before the asset fails."
📌 Immediate PoC — AGCO Corporation
During a recent engagement with AGCO — one of the world's largest agricultural OEMs (Fendt, Massey Ferguson, Challenger, Valtra) — it emerged that AGCO is adopting Servigistics for global service parts planning. They will have a world-class planning tool and no AI execution layer to act on it.
AGCO Profile
4 global brands · 75+ countries · Agricultural OEM · Complex aftermarket parts network
PoC Proposal
LTTS delivers OptiChain AI on top of AGCO's Servigistics. 90 days. Document MTTR, SLA, ROI outcomes.
📈 Partnership Commercial Models
Model A — ISV Co-Sell (Recommended)
OptiChain on PTC Marketplace · PTC AMs refer customers · 15-20% referral fee on ARR · LTTS pays 8-12% back on new Servigistics licenses · Average deal $320K impl + $220K ARR
Model B — White Label OEM
PTC offers as "Servigistics AI Execution" module · 22-28% royalty to LTTS · $80-120K ARR add-on · LTTS preferred SI
Model C — Co-Innovation JV (Year 2+)
Joint product: Servigistics METRIC/VARI-METRIC + OptiChain AI execution · Announce at Liveworx 2027
💰 3-Year Financial Model — Model A (ISV Co-Sell)
| Metric | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| Joint customers landed | 12 | 28 | 52 |
| OptiChain SaaS ARR (cumulative) | $2.5M | $9.1M | $17.2M |
| LTTS implementation revenue | $3.6M | $5.6M | $6.8M |
| New Servigistics licenses via LTTS | 4 | 8 | 14 |
| Servigistics TCV for PTC | $1.6M | $3.2M | $5.6M |
| LTTS total revenue (cumulative) | $6.1M | $14.7M | $24.0M |
6
Bidirectional Tables
3 IN · 3 OUT
500+
Servigistics Customers
Addressable via PTC
AGCO
First PoC Target
Active conversation
$24M
LTTS Revenue Y3
Cumulative projection
90 days
PoC Delivery
Integration live today
🗃 BigQuery Data Warehouse
All OptiChain data stored and processed natively in Google BigQuery — no data leaves the Google ecosystem
3.4 TB · 99.9% uptime
Total Data Stored
3.4 TB
Across 5 datasets
Queries/Day
14,200
Avg: 1.2s latency
Reserved Slots
2,000
Flat-rate commitment
Data Freshness
< 3s
Streaming inserts
📊 Dataset Overview — optichain-ai project
| Dataset | Tables | Size | Partitioned | Retention | Access |
|---|---|---|---|---|---|
| raw_d365 | 18 | 2.4 TB | By date | 90 days | Internal |
| processed_supply_chain | 24 | 890 GB | By date+SKU | 2 years | Internal |
| analytics_inventory | 12 | 120 GB | By month | 5 years | Analysts |
| ml_features | 8 | 44 GB | By model | 1 year | Vertex AI |
| predictions_output | 6 | 8 GB | By run date | 6 months | Vertex AI |
🏭 Supplier Management
AI-scored supplier intelligence — performance, risk, contracts, ESG & alternative sourcing
Total Suppliers
24
8 categories
Avg OTD
91.4%
↑ +2.1% YoY
Avg Quality
96.8%
Target: 98%
At Risk
3
Needs action
Total Spend
$4.2M
This quarter
Contracts Expiring
4
Next 90 days
📋 Supplier Scorecard
All
At Risk
Critical
| Supplier | Category | OTD % | Quality | Lead Time | AI Score | Risk | Status |
|---|---|---|---|---|---|---|---|
SUP002 — Reliable Resources Steel · Primary · Kansas City |
Steel | 97% | 99% | 5d | 97.2 | LOW | PREFERRED |
SUP006 — MidWest Components Welding · Qualified · Chicago |
Welding | 94% | 97% | 4d | 91.8 | LOW | APPROVED |
SUP004 — Pacific Supply Group Valves · Approved · Los Angeles |
Valves | 82% | 95% | 9d | 76.4 | MEDIUM | APPROVED |
SUP001 — Global Metals Inc. Steel · Primary · Shanghai |
Steel | 77% | 89% | 8.3d | 68.1 | HIGH | BLOCKED |
SUP003 — Asian Components Electronics · Primary · Taipei |
Electronics | 61% | 88% | 12d | 52.3 | CRITICAL | AT RISK |
SUP008 — Atlas Global Metals Steel · Potential · Toronto |
Steel | N/A | N/A | 12d | — | N/A | EVAL REQ'D |
💵 Spend Analytics — Q2 2025
SUP002 — Reliable Resources
$1.42M
SUP001 — Global Metals
$1.08M
SUP004 — Pacific Supply
$740K
SUP003 — Asian Components
$620K
SUP006 — MidWest Components
$340K
Spend by Category
48%
Steel
15%
Electronics
18%
Valves
8%
Welding
📈 On-Time Delivery Trend — Last 8 Weeks
SUP002 (97%)
SUP004 (82%)
SUP001 (77% ↓)
⚠ Supplier Risk Matrix
LOW IMPACT
MED IMPACT
HIGH IMPACT
HIGH PROB
SUP006
SUP001
SUP003 ⚠
MED PROB
SUP004
LOW PROB
SUP002
SUP008
SUP008
📄 Contract Status
SUP002 — Reliable Resources
ACTIVE
3-year MSA · Expires Dec 2026 · $4.2M value
Auto-renewal clause active
SUP001 — Global Metals
EXPIRING
Annual PO framework · Expires Mar 2025 · Review pending
⚠ 45 days to expiry — negotiate or replace
SUP003 — Asian Components
AT RISK
Spot purchase only · No MSA in place · High exposure
⚠ No contract coverage — escalation required
SUP004 — Pacific Supply
ACTIVE
2-year supply agreement · Expires Sep 2025
Renewal discussions due Q2 2025
🔄 Alternative Sourcing Map
SKU-BEAM-001 (Steel Beam)
● SUP001 (Primary — BLOCKED)
8.3d
● SUP002 (Alternate — ACTIVE)
5d
● SUP008 (Eval — PENDING)
12d
SKU-VALVE-3IN (Gate Valve)
● SUP004 (Primary — MEDIUM)
9d
● SUP002 (Alternate — ACTIVE)
6d
SKU-CABLE-ELEC (Electronics)
● SUP003 (Primary — CRITICAL)
12d
● No qualified alternate ⚠
—
🤖
AI Sourcing Recommendations
URGENT
Qualify SUP008 (Atlas Global) to replace SUP001 for SKU-BEAM — saves $120K/yr & removes geopolitical risk
URGENT
Source alternate electronics supplier for SKU-CABLE-ELEC — SUP003 single-source creates $62K exposure
THIS WEEK
Renew SUP001 contract or switch to SUP002 — 45 days to expiry, no fallback PO in place
OPTIMISE
Consolidate SUP004 valve orders — 3 split POs this quarter; consolidation saves est. 6% on unit cost
LONG TERM
Increase SUP002 share-of-wallet to 40% — highest ESG score + best OTD aligns with 2026 sourcing policy
🚀 Supplier Onboarding Pipeline
✓
Discovery
SUP008 identified
via AI sourcing
via AI sourcing
DONE
✓
RFI Sent
Capability &
capacity confirmed
capacity confirmed
DONE
⚡
Qualification
Quality audit
scheduled Feb 28
scheduled Feb 28
IN PROGRESS
📄
Contract
MSA draft
pending legal
pending legal
PENDING
📦
First Order
Trial PO
planned Q2 2025
planned Q2 2025
PLANNED
Supplier Scorecard
| Supplier | Category | On-Time % | Quality % | Lead Time | AI Score | Risk |
|---|---|---|---|---|---|---|
| Reliable Resources Ltd. | Steel | 97% | 99% | 4d | 97.2 | Low |
| Component Solutions | Mixed | 94% | 96% | 6d | 84.1 | Low |
| Pacific Supply Co. | Copper | 82% | 88% | 9d | 72.4 | Med |
| Global Metals Inc. | Steel/Al | 77% | 91% | 8.3d | 61.3 | High |
🌿 Sustainability & ESG Tracking
Carbon footprint · ESG compliance · Net Zero roadmap · Supplier sustainability · Circular economy
On Track — Net Zero 2040
CO₂ Emissions
142 kt
↓ −18% YoY
ESG Score
82/100
↑ +7 pts YoY
Renewable Energy
61%
Target: 80% by 2026
Green Suppliers
68%
↑ +4% vs target
Water Usage
3.2 ML
↓ −9% vs 2023
Waste Diverted
87%
Landfill-free target: 95%
🏭 Carbon Emissions — Scope 1 / 2 / 3
ktCO₂e · GHG Protocol aligned
Scope 1
Direct emissions (fleet, facilities)
28 kt
↓ −12% vs last year | Target: 22 kt by 2025
Scope 2
Purchased electricity & heat
34 kt
↓ −22% (renewable energy switch) | Target: 18 kt by 2026
Scope 3
Supply chain, logistics, end-of-life
80 kt
⚠ Largest source — supplier engagement programme active
Total CO₂e trend (ktCO₂e) — 2019 to 2025
🌟 ESG Scorecard
E — Environmental
88
Carbon Reduction ✓
Renewable Energy ✓
Biodiversity ⚠
S — Social
76
Labour Standards ✓
DE&I ✓
Community Impact ⚠
G — Governance
82
Board Oversight ✓
Anti-corruption ✓
Transparency ✓
Overall ESG Rating: B+ (82/100)
Top quartile for industrial supply chains · MSCI rating: AA
🎯 Net Zero Roadmap — 2024 to 2040
SBTi Aligned
✓
2024
Baseline set
GHG audit
GHG audit
COMPLETE
⚡
2025
80% renewable
energy target
energy target
IN PROGRESS
🏭
2026
Scope 3
supplier audit
supplier audit
PLANNED
☰
2028
50% emission
reduction (vs 2019)
reduction (vs 2019)
PLANNED
♻
2035
Zero landfill
circular ops
circular ops
PLANNED
▲
2040
Net Zero
across all scopes
across all scopes
TARGET
🏭 Supplier ESG Ratings
| Supplier | E | S | G | Overall | Status |
|---|---|---|---|---|---|
SUP001 — Global Metals Steel · Primary |
62 | 74 | 80 | B− | IMPROVING |
SUP002 — Reliable Resources Multi-SKU · Approved |
88 | 85 | 90 | A | CERTIFIED |
SUP003 — Asian Components Electronics · Primary |
44 | 58 | 65 | C+ | AT RISK |
SUP004 — Pacific Supply Group Valves · Approved |
77 | 72 | 68 | B+ | COMPLIANT |
SUP006 — MidWest Components Welding · Qualified |
82 | 79 | 84 | A− | CERTIFIED |
📄 Regulatory & Framework Compliance
EU CSRD
Corporate Sustainability Reporting
GHG Protocol
Scope 1 + 2 + 3 reporting
SBTi
Science Based Targets initiative
CDP Climate
Carbon Disclosure Project
TCFD
Climate risk disclosures
EU Taxonomy
Sustainable finance classification
ISO 14001
Environmental management system
🌳 Carbon Offset Portfolio
Total offsets purchased
38 kt
Amazon Reforestation
Brazil · VCS certified
18 kt
$54K/yr
Wind Farm — India
Rajasthan · Gold Standard
12 kt
$28K/yr
Soil Carbon — US
Kansas · ACR certified
8 kt
$19K/yr
Net position: 142 kt emitted − 38 kt offset = 104 kt remaining
♻ Circular Economy Metrics
Recycled input materials34%
Target: 50% by 2027
Recycled packaging72%
Target: 100% by 2026
Product return / refurb rate18%
Target: 30% by 2026
Waste diverted from landfill87%
Target: 95% by 2025
Water recycled in operations43%
Target: 60% by 2027
🤖
AI ESG Recommendations
HIGH IMPACT
Replace SUP003 (C+ rating) with a qualified green supplier — projected -8.4 kt CO₂ reduction
MEDIUM IMPACT
Switch WH-EAST to renewable energy contract — estimated -6.2 kt Scope 2 reduction
QUICK WIN
Consolidate PLT-CENT → WH-SOUTH transfers to reduce transport runs — saves 420 tCO₂/yr
COMPLIANCE
EU Taxonomy review due Q1 2025 — 3 activities pending do-no-significant-harm assessment
📦 Carbon Intensity by SKU — tCO₂e per 1,000 units
LCA methodology · ISO 14044
SKU-PUMP-CENT
18.4
tCO₂e / 1k units
▲ HIGH
SKU-VALVE-3IN
11.2
tCO₂e / 1k units
▲ MEDIUM
SKU-BEAM-001
8.7
tCO₂e / 1k units
▲ MEDIUM
SKU-WELD-ROD
2.1
tCO₂e / 1k units
▼ LOW
SKU-CABLE-ELEC
1.4
tCO₂e / 1k units
▼ LOW
Carbon Footprint (MTons CO2)
142
↓ −18% YoY
Sustainable Sourcing %
68%
▲ +4% vs target
ESG Supplier Score (avg)
B+
Up from B last year
Recycled Materials %
34%
▲ +6% vs Q2
🌱 AI Sustainability Recommendation
Switching 40% of Global Metals spend to Reliable Resources Ltd. (ESG: A+) would reduce supply chain carbon footprint by an estimated 12 MTons CO2 annually while also reducing cost risk by $89K.
✅ This action serves both financial and ESG objectives simultaneously — recommended for Q3 execution.
🎯 SKU Monitoring Agents
Create AI agents that monitor SKUs using natural language rules — auto-alerts, reorder triggers, risk escalation
Live Data Context
Inventory Value$915,407
Active Stockouts12
SKUs Below Reorder8
Supplier Alerts3
Pending POs5
Forecast Accuracy92.1%
Risk Snapshot
CRITICAL
SKU-BEAM-001: 4.2 days supply
HIGH
SUP001 delivery rate 77%
HIGH
3 sole-source dependencies
Recent Topics
No conversations yet
🚦 Supplier Risk Network Graph
Dependency mapping — visualize sole-source risks and cascade exposure
3
Critical Nodes
7
High Risk Links
24
Total SKUs
$88K
Cascade Exposure
Critical
Warning
Healthy
Node Details
Click any node to inspect
Risk Alerts
SUP001 sole-source: 8 SKUs, $88K
SUP003 degraded 23%, 4 SKUs
WH-NORTH at 94% capacity
Top Recommendations
1. Qualify SUP005 as backup for SKU-BEAM-001
2. Redistribute WH-NORTH load to WH-WEST
3. Dual-source SKU-CABLE-4AWG urgently
🔀 Procurement Scenario Workspace
Compare procurement strategies side-by-side with AI scoring
🔴
Active Decision: Steel Beam Procurement — SUP001 Degradation
SKU-BEAM-001 · Days of supply: 4.2 · Budget: $50,000
🤖 AI Comparative AnalysisClick AI Scoring to analyze
| METRIC | SCENARIO A | SCENARIO B | SCENARIO C |
|---|---|---|---|
| Total Cost | $44,400 | $38,200 | $41,800 |
| Lead Time | 8.3 days | 14 days | 5 days |
| Stockout Risk | HIGH | MEDIUM | LOW |
| Supplier Reliability | 77% | 94% | 99% |
| AI Confidence | — | — | — |
| Recommendation | — | — | — |
🌏 Geopolitical Risk Scenarios
Plant shutdowns · Shipment disruptions · AI-ranked recovery options · Live ERP write-back
2 ACTIVE DISRUPTIONS
| $306K at risk
📡 Live Geopolitical Intelligence Feed
Not yet loaded
Click Fetch Live Feed to pull latest shipping & trade intelligence
⚠
Scenario 1 — Plant Shutdown
PLT-CENT Kansas City · Odoo ERP
$177K
Revenue at Risk
3
Orders Affected
8–12d
Recovery Est.
3
Recovery Options
[Odoo] Odoo ERP
[D365] D365 PO
AI recovery ready
▶ Click to expand recovery plan
🚥
Scenario 2 — Shipment Blockage
SUP001 PO-2891 · Shanghai Port · D365
$129K
Revenue at Risk
2
Orders Affected
5–7d
Recovery Est.
3
Recovery Options
[D365] D365 PO Flagged
[Odoo] Alt. Supplier Ready
AI recovery ready
▶ Click to expand recovery plan
🏭 Service Network Digital Twin
Live virtual replica of the entire aftermarket service network — depots, vans, inventory positions, technicians, and asset health — updated in real time from IoT, D365, and Fuse Connect
Live · 30s refresh
4 Depots · 14 Vans · 1,240 Assets
Network Health Score
91.4%
All depots operational · 2 vans offline
Fill Rate — Network Wide
93.1%
↑ 15pt from 78% SRV baseline
Parts In Transit
47
Transfers between echelon levels
Assets at Risk
8
Failure prob >60% · Parts pre-staged for 6
Open Work Orders
24
6 at SLA risk · 1 escalated to VP
SLA Compliance (live)
94.8%
Target: 95% · 1 breach this week
📋 Procure-to-Pay Intelligence
AI-driven P2P automation — demand signal to supplier PO to invoice match to payment in one connected workflow
P2P Engine Active
Open Requisitions
14
3 pending approval
Active POs
28
$2.4M total value
Invoices Pending Match
7
$186K value
Payments Due
$340K
Next 7 days
Cycle Time Saved
3.8d
vs manual average
🔄 End-to-End P2P Workflow
Live · Last updated 4 min ago
📝
Requisition
14 open
🏭
Sourcing & RFQ
AI-scored
📦
Purchase Order
28 active
✅
Goods Receipt
GRN match
📃
Invoice Match
3-way match
💰
Payment
$340K due
📝 Purchase Requisition
AI-generated requisitions from inventory signals — approve, amend or reject before PO creation
14
Open
3
Pending Approval
8
Approved This Week
$284K
Total Value Open
🏭 Sourcing & RFQ
AI-scored supplier selection — RFQ management, bid comparison and award recommendation
📦 Purchase Orders
AI-generated POs with dual Odoo + D365 write-back — track status from issue to delivery
28
Active POs
$2.4M
Total Open Value
4
Overdue Deliveries
91%
On-Time Delivery Rate
✅ Goods Receipt & Inspection
Record deliveries, inspect against PO, update inventory and trigger 3-way match
12
GRNs This Month
2
Pending Inspection
1
Discrepancies
98%
Acceptance Rate
📃 Invoice Matching
AI-powered 3-way match: Purchase Order → Goods Receipt → Supplier Invoice — with D365 AP integration
19
Auto-Matched
7
Pending Review
2
Exceptions
92%
Auto-Match Rate
💰 Payment & Approval Workflow
Multi-level approval routing, spend governance and D365 AP payment release
$340K
Due in 7 days
5
Awaiting Approval
$1.2M
Paid This Month
2.1d
Avg Approval Time
Approval Policy Thresholds
Auto-approve
AI-matched · no variance
< $5K
Procurement Manager
Single approver
$5K–$25K
CFO Sign-off
Two-level approval
> $25K
Board approval
Strategic procurement
> $250K
📈 P2P Spend Analytics
AI-powered spend intelligence — category analysis, supplier concentration, savings and compliance
$2.26M
Total Spend YTD
$184K
Savings Identified
94%
PO Coverage
3
Supplier Risks Flagged
Spend by Supplier
Global Metals Inc.$842K (37%)
⚠ High concentration risk
Reliable Resources$504K (22%)
MidWest Components$410K (18%)
Pacific Supply Group$318K (14%)
Others$186K (9%)
🤖 AI Savings Opportunities
CONSOLIDATE STEEL ORDERS
Combine 3 separate steel orders into quarterly blanket PO with Global Metals — projected saving $62K (7.4%)
DUAL-SOURCE VALVES
Add Pacific Supply Group as second valve supplier — reduces concentration risk and unlocks 8% volume discount · $40K saving
EARLY PAYMENT DISCOUNT
Reliable Resources offers 2/10 net 30 terms — paying 8 invoices early this month captures $18K discount
🤖 AI-Powered Demand-Driven Requisition Engine
Scans inventory positions, demand forecasts and reorder triggers — generates draft requisitions automatically for buyer approval
Engine Running — Last scan: 4 min ago
🤖
How the engine works
Every 15 minutes the engine reads the 6-state inventory classification across all sites and both ERPs. Any SKU entering CRITICAL or SHORTAGE state triggers a draft requisition pre-filled with the optimal supplier (from RFQ history and ESG scores), recommended quantity (LP-computed), urgency level, and business justification. Buyers approve in one click — the engine raises the PO and writes back to Odoo and D365 automatically.
47
Auto-reqs this month
3.8d
Avg cycle saved
🤝 Supplier Collaboration Portal
PO acknowledgements, ASNs, delay notifications and ETA updates from suppliers — live into inventory and risk engines
5
Connected Suppliers
14
POs Acknowledged
2
Delay Notifications
8
ASNs Received
📄 Contract Management & Compliance
Blanket PO tracking, contract utilisation, price tolerance alerts and maverick spend detection
11
Active Contracts
3
Expiring in 90 days
2
Price Tolerance Breaches
94%
Spend Under Contract
🛠 Multi-Level Approval Workflow Builder
Configure approval routing by spend threshold, category, cost centre or supplier risk — enforced on every PO and invoice
Approval Performance This Month
68%
Auto-approved
2.1d
Avg approval time
4
SLA breaches
$2.4M
Total approved
Audit Trail — Last 5 Actions
INV-2891 auto-approved · $44,4002h ago
PO-4422 approved by J. Smith · $29,4004h ago
REQ-1042 escalated to CFO · $140K6h ago
PO-4388 held by Risk Guardian · overdue1d ago
⚡ Early Payment & Dynamic Discounting
Identify invoices where early payment yields better return than holding cash — ranked payment run with D365 AP execution
$18K
Discounts Available Now
8
Eligible Invoices
36.5%
Annualised Yield
$84K
Saved YTD
🤖 AI Payment Run Recommendation
Paying INV-2891 and INV-2887 today captures $1,652 in discounts on $82,600 of spend — equivalent to a 36.5% annualised yield, which exceeds the current cost of capital at 8.2%. Total cash outflow today: $81,060. The model recommends executing both payments before 5pm to meet the 2/10 discount window.
📊 Spend Forecasting & Budget Guardrails
ML-based forward spend projections by category and cost centre — with real-time budget alerts before breaches occur
$4.8M
Full-Year Budget
$2.26M
Spent YTD
$4.62M
AI Full-Year Forecast
1 at risk
Budget Breach Alerts
Category Budget vs Forecast
Steel & Metals
Budget: $1.6MForecast: $1.74M ▲+9%
⚠ On track to breach by $140K — activate cost levers
Industrial Valves
Budget: $900KForecast: $840K ↓-7%
Pumps & Equipment
Budget: $800KForecast: $792K
Electrical & Cable
Budget: $600KForecast: $524K ↓-13%
⚠ Budget Alerts & AI Corrective Actions
BREACH RISK — Steel & Metals · $140K overspend forecast
Current run-rate implies $1.74M full-year spend against $1.6M budget. Driven by $0.08/kg steel price increase since Q1 and 3 emergency POs outside blanket contract.
AI Recommended Levers:
✓ Consolidate Q3 orders into blanket PO — saves ~$62K
✓ Reroute 20% volume to SUP002 at lower contracted rate — saves ~$41K
✓ Defer 2 non-critical orders to Q1 2026 — removes $38K from current year
UNDER BUDGET — Electrical & Cable (-13%)
$76K budget headroom available. AI recommends pre-buying Q4 cable stock at current pricing to lock in before projected +8% cost increase in October.
🌿 Carbon-Cost PO Scoring
Carbon footprint of every purchase order — Scope 3 Cat 1 cost alongside financial cost, with green alternative surfacing
142 kt
Total Scope 3 Cat 1 YTD
$28/t
Internal Carbon Price
18.4t
Highest SKU — PUMP
3
Green Alternatives Ready
🤖 Green Alternative — PO-4422 · SKU-PUMP-CENT
Current: MidWest Components
$29,400 · 220.8 tCO₂e · Total $35,582
→
Alt: EcoTech Pumps (SUP009) — EV-certified
$31,200 (+$1,800) · 44.2 tCO₂e · Total $32,636 · Saves $2,946 fully-costed
🔍 Tail & Maverick Spend Intelligence
AI classifier identifies off-contract buying, one-off purchases and consolidation opportunities across all transactions
$340K
Tail Spend (15%)
$128K
Maverick / Off-Contract
$94K
Consolidation Savings
847
Tail Transactions
Consolidation Opportunities
CONSOLIDATE MAINTENANCE PARTS
Move 14 tail vendors to SUP006 MidWest Components framework · Annual saving: $38K
FREIGHT BLANKET CONTRACT
Send RFQ to top 3 logistics providers for annual blanket · Estimated saving: $18K
IT SUBSCRIPTION AUDIT
6 duplicate SaaS subscriptions identified · Cancel duplicates: $8.4K saving
🚨 Supplier Financial Health & Risk Scoring
Credit ratings, news sentiment, financial signals and tariff exposure — composite risk score updated daily
1
Critical Risk Supplier
2
Elevated Risk
3
Low Risk
$842K
Spend at Critical Risk
SUP001 — Global Metals Inc.
Primary · Steel · $842K annual spend
88
CRITICAL RISK
CCC
Credit Rating
-28%
Revenue YoY
77%
OTD Rate
High
Tariff Exposure
⚠ AI Alert: News sentiment negative — 3 articles this week reference late payments to sub-suppliers. Shanghai operations under port congestion stress. Revenue down 28% YoY. Recommend reducing single-source dependency immediately.
SUP002 — Reliable Resources Ltd.
Approved · Multi-SKU · $504K annual spend
18
LOW RISK
A+
Credit Rating
+12%
Revenue YoY
97%
OTD Rate
Low
Tariff Exposure
SUP006 — MidWest Components
Preferred · Welding & Equipment · $410K annual spend
22
LOW RISK
📁 Document Repository
Versioned storage for every PO, invoice, GRN, contract and RFQ — searchable, auditable, downloadable
28
Purchase Orders
47
Invoices
31
GRNs
11
Contracts
9
RFQs
Filter:
🤖 Invoice OCR & AI Parsing
Upload supplier invoice PDF or image — Claude Vision extracts all fields and pre-populates the 3-way match automatically
📄
Drop invoice PDF or image here
PDF, JPG, PNG supported · Max 10MB · Claude Vision AI extraction
💡 Demo: Simulate OCR Extraction
Click to simulate Claude Vision parsing a real supplier invoice
📤 Purchase Order Dispatch
Generate formatted PO documents and dispatch to suppliers by email or portal notification with acknowledgement tracking
5
Awaiting Dispatch
18
Dispatched This Month
14
Acknowledged
4
No Response >48h
✏️ Digital Signatures & Approval Stamps
Timestamped, legally binding approvals on contracts, high-value POs and payment releases with full audit trail
9
Signed This Month
3
Awaiting Signature
1
Expired — Resend
100%
Legally Binding
Signature Policy
<$5K — Auto-stamped (system user)
$5K–$25K — Procurement Manager digital signature
>$25K — CFO + Finance Director dual signature
Contracts — Legal + CFO + counterparty signature
Every signature is cryptographically hashed, timestamped to UTC and stored immutably with signer IP address, device fingerprint and user ID — admissible in any jurisdiction recognising electronic signatures.
🔁 EDI Integration Hub
ANSI X12 & EDIFACT transaction handling — 850 PO · 855 ACK · 856 ASN · 810 Invoice · real-time mapping to platform data model
2
EDI Partners
847
Transactions This Month
3
Failed / Errors
99.6%
Success Rate
🌐 Multi-Currency & Tax Handling
Real-time FX conversion, VAT/GST calculation, withholding tax and country-specific tax codes on every PO and invoice
💸 Live Exchange Rates — Updated every 4h
USD/EURUS Dollar / Euro
0.9241
↑ +0.12%
USD/GBPUS Dollar / Pound
0.7882
↓ -0.04%
USD/CNYUS Dollar / Yuan
7.2641
↑ +0.08%
USD/AEDUS Dollar / Dirham
3.6725
Pegged
USD/INRUS Dollar / Rupee
83.42
↑ +0.31%
Tax Code Matrix
United StatesNo federal VAT
State sales tax applicable · B2B exempt for most industrial goods · Form W-9 required
Germany / EUVAT 19% / 7%
Reverse charge on B2B intra-EU · EC Sales List filing required · CBAM for steel imports
UAEVAT 5%
Standard rate · Industrial zero-rated exemptions · VAT return quarterly
IndiaGST 18% / 5%
CGST + SGST / IGST on inter-state · HSN codes required on all invoices
ChinaVAT 13% / 9%
Special VAT fapiao required · Withholding tax 10% on service payments · SAFE approval for FX
📄 GL Coding & ERP Posting
Assign general ledger accounts and cost centres to every approved invoice before D365 / Odoo journal entry posting
6
Awaiting GL Code
21
Posted This Month
94%
AI Auto-Coded
$1.2M
Posted YTD
📊 Budget Commitment & PO Encumbrance
Real-time budget reservation on PO creation — committed spend tracked alongside invoiced and paid to show true budget position
Budget Position — Full Year
Total Budget$4,800,000
Invoiced & Paid $2,260KCommitted (PO) $1,840KAvailable $700K
■ Invoiced 47%■ Committed 38%■ Available 15%
Invoiced & Paid$2,260,000
Committed — Open POs$1,840,000
Open Requisitions$284,000
True Available$416,000
⚖️ Dispute Management
Formal dispute workflow — log, track, resolve and credit note supplier invoice discrepancies with full case history
2
Open Disputes
1
Awaiting Supplier Response
8
Resolved YTD
$28K
Credit Notes Received
🏭 Vendor Master Management
Supplier onboarding, bank account verification, tax ID validation, sanctions screening and preferred supplier list
18
Approved Vendors
2
Pending Verification
0
Sanctions Matches
5
Preferred Suppliers
📋 Audit Log & Compliance Reporting
Immutable record of every P2P action — who, what, when, from where — exportable for SOX, ISO 27001 and internal audit
4,847
Events This Month
100%
Immutable Record
7 yrs
Retention Policy
0
Policy Violations
Filter:
🔗 Supply Chain Digital Twin
Virtual replica of the entire supply chain — real-time visibility, prediction and autonomous optimisation across all 11 dimensions
Twin Live — 35,000+ data points/min
🚚 Visibility
📦 Inventory
🏭 Production
🚢 Logistics
🌍 Scenario
📊 Demand
🤝 Suppliers
📌 Fulfillment
⚡ Sustainability
💹 Cost-to-Serve
🤖 AI Twin
📋 Order Management
Live customer orders — AI fulfillment risk scoring and ATP status
47
Open Orders
8
At Risk
$284K
Revenue at Risk
94.1%
Perfect Order Rate
3.2d
Avg Order-to-Ship
Active Customer Orders
| ORDER ID | CUSTOMER | SKU | QTY | VALUE | PROMISE DATE | RISK | SCORE | ACTION |
|---|
🚚 Fulfillment Risk Dashboard
Real-time fulfillment gap analysis — inventory vs open order demand
📈 OTIF Trend — Last 8 Weeks
🎯 O2C Cycle Time
✅ Available-to-Promise Engine
Verify fulfilment feasibility before confirming any customer order — live stock, transit and lead-time check
✅
Ready to check availability
Fill in the order details on the left and click Run ATP Check
📈 Revenue Protection
AI-driven revenue risk monitoring — identify and protect at-risk orders
$2.4M
Total Pipeline
$2.1M
Protected
$284K
At Risk
$198K
Recoverable
Revenue Risk by Root Cause
🤔 AI Recovery Actions
👥 Customer 360° View
Complete account intelligence — orders, contracts, risk, financials and D365 CRM in one screen
Select Account
—
12 accounts
👥
Select an account to view their 360° profile
Orders · Contracts · Risk · Financials · Contact details · Exceptions
💌 Email Auto-Indexing
Document AI reads incoming customer emails and extracts PO details automatically
3
Unprocessed
12
Auto-indexed
8s
Avg Extract Time
98.4%
Extraction Accuracy
🤖 AI Extraction Result
Click an email to see extraction preview
✅ Order Validation Engine
Auto-validates every order: inventory, credit, pricing, ATP — routes exceptions instantly
🚚 Logistics Tracking
Real-time shipment visibility — carrier status, ETAs, and exception escalation
34
Active Shipments
26
On Schedule
6
Delayed
2
Exception
3.2d
Avg Transit
📄 Contract Lifecycle Management
Track expiry dates, volume commitments, SLA performance and renewal workflows
18
Active Contracts
3
Expiring in 30d
2
Volume at Risk
$4.8M
Total Value
💰 Invoice & GRN Matching
3-way match: Purchase Order ↔ Goods Receipt ↔ Invoice — auto-release on match
28
Pending Match
21
Auto-Matched
4
Exceptions
$312K
Pending Payment
$1.2M
Released This Month
⚠️ Exceptions & Case Management
Every supply chain exception — assigned, tracked, resolved with full audit trail
🔄 Workflow Automation
Configure approval chains, escalation rules and SLA thresholds — no code required
🗃 Data Lake & Integration
QAD EE + Dynamics 365 + Odoo → Stage Tables → BigQuery Lake · Real-time pipeline visibility · Table explorer
QAD + D365 + Odoo Live
🔄 End-to-End Data Integration Pipeline
Aftermarket & Service Parts Intelligence
5 AI Agents · 1,240 assets monitored · Multi-echelon inventory · Servigistics integration active · GCP / Vertex AI
All Agents Operational
Servigistics Sync: 02:00 UTC
Last updated:
SLA Compliance
96.1%
↑ from 81.0% · 12 mo trend
MTTR Reduction
34%
6.1d → 4.0d avg resolution
Return on Investment
4.8×
$184K penalties avoided YTD
Parts Fill Rate
93.4%
SRV target: 94% · 1,240 SKUs
Failure Warning Lead
18 days
LSTM model · 91.4% accuracy
Dispatch Decision
<500ms
WO assignment · 7 technicians
Agent Status — Live
5 / 5 Running
| Agent | Status | Last Action | Queue |
|---|---|---|---|
| IoT Anomaly Agent | Active | A-001 vibration alert · 09:42:18 | 3 alerts |
| Failure Prediction Agent | Active | SIG-2025-0881 issued · 09:41:30 | 82% risk |
| Parts Replenishment Agent | Active | TRF-0081 dispatched · 09:41:30 | 2 open POs |
| WO Dispatch Agent | Active | WO-4441 → M. Johnson · 09:41:30 | 4 active WOs |
| SLA Guardian Agent | Active | WO-4441 · 5h 58m remaining | 4 clocks |
Active Work Orders
4 open
| WO # | Asset | Technician | SLA Clock | Status |
|---|---|---|---|---|
| WO-4441 | A-001 · HOU-01 Compressor · Bearing |
M. Johnson | 5h 58m 8h SLA |
In Progress |
| WO-4439 | A-006 · MID-03 Pump · Impeller |
S. Ahmed | 2h 15m 4h SLA |
At Risk |
| WO-4435 | A-009 · MID-03 Motor · Winding |
R. Kumar | 11h 40m 24h SLA |
Scheduled |
| WO-4433 | A-018 · DAL-02 Pump · Bearing |
L. Wong | Closed SLA met ✓ |
Closed |
Depot Inventory — Actual vs Servigistics Target
↓ SRV target nightly
↑ OC position 6-hourly
| Depot | SKU | Description | SRV Target | On Hand | In Transit | Available | Fill Rate | OC Action | SRV Signal |
|---|---|---|---|---|---|---|---|---|---|
| HOU-01 | NSK-6309-2RS | Deep Groove Ball Bearing 45mm | 5 | 2 | 4 → | 2 | 40% | TRF-0081 dispatched | SIG-2025-0881 ↑ |
| MID-03 | PRT-D001 | Impeller 6" Centrifugal | 3 | 0 | 2 → | 0 | 0% | PO-AM-0445 + TRF-0082 | SIG-2025-0880 ↑ |
| DAL-02 | NSK-6205-ZZ | Single Row Ball Bearing 52mm | 12 | 14 | 0 | 14 | 116% | No action required | SRV plan adopted |
| AUS-04 | NSK-7310-B | Angular Contact Bearing 110mm | 4 | 3 | 0 | 3 | 75% | PO-AM-0447 pending | SRV ROP triggered |
| DAL-02 | NSK-NU316-E | Cylindrical Roller Bearing 170mm | 2 | 3 | 0 | 3 | 150% | No action required | SRV plan adopted |
Servigistics Integration Health
Live
↓ Incoming Tables
srv_safety_stock 1,240 rows
srv_demand_forecast 3,720 rows
srv_stock_targets 4,960 rows
Last sync: today 02:00 UTC ✓
↑ Outgoing Tables
oc_failure_signals 247 YTD
oc_actual_consumption on WO close
oc_inventory_position 6-hourly
Last sent: today 12:00 UTC ✓
Forecast Accuracy — OC vs SRV Croston
SRV Croston
78%
OC + IoT Signal
94%
+16pp uplift from LSTM failure prediction signals fed back to SRV demand history
Recent Failure Signals — Sent to Servigistics
247 YTD
| Signal | Asset · SKU | Risk | OC → SRV Action | Sent |
|---|---|---|---|---|
| SIG-2025-0881 | A-001 · NSK-6309-2RS Bearing Fatigue · HOU-01 |
82% | Pre-stage 8 units SRV planned 3 units |
09:41 ✓ |
| SIG-2025-0880 | A-006 · PRT-D001 Impeller Wear · MID-03 |
78% | Pre-stage 5 units SRV planned 1 unit |
09:38 ✓ |
| SIG-2025-0879 | A-009 · NSK-22220-K Winding Degradation · MID-03 |
71% | Expedite PO SRV planned 2 units |
08:50 ✓ |
| SIG-2025-0877 | A-012 · NSK-NU316-E Roller Fatigue Early · DAL-02 |
34% | Monitor No SRV override needed |
Yesterday ✓ |
OptiChain AI · Platform Overview
GCP · Vertex AI · BigQuery · optichain-ai
📡
IoT Anomaly
1,240 sensors
Active
🧠
Failure Prediction
LSTM · 18d lead
3 at risk
📦
Parts Replenishment
EOQ · Croston · VMI
2 low stock
🔧
WO Dispatch
<500ms · 7 techs
4 active WOs
⏱
SLA Guardian
96.1% · $184K saved
All on track
About OptiChain AI Aftermarket
OptiChain AI Aftermarket is an autonomous service-parts intelligence platform from L&T Technology Services that transforms reactive, break-fix maintenance into predictive, agent-driven operations. Five specialized AI agents work continuously across the aftermarket lifecycle — detecting equipment degradation weeks before failure, pre-positioning parts ahead of demand, assigning the optimal field technician in under 500 milliseconds, and monitoring every SLA clock in real time. The platform integrates bidirectionally with PTC Servigistics: reading safety stock targets, demand forecasts, and ABC/XYZ classifications nightly, and sending back actual consumption records and LSTM failure signals that improve Servigistics' Croston demand model over time. Deployments consistently deliver a 34% reduction in MTTR, SLA compliance improvement from 81% to 96.1%, a 4.8× return on investment, and over $184K in SLA penalties avoided annually.
PARTNERSHIP
PTC · Servigistics Integration
"Servigistics tells you what to stock.
OptiChain makes sure it's there before the asset fails."
OptiChain makes sure it's there before the asset fails."
6
Bidirectional Tables
94%
Forecast Accuracy
$24M
LTTS Revenue Y3
3 IN tables (nightly) · 3 OUT tables (event-triggered) · AGCO PoC ready
View Integration →
Multi-Echelon Inventory Optimisation
Central WH → Regional Depot → Field Van · Mirrors Servigistics echelon model exactly
Central WH
→
4 Depots
→
Field Vans
SRV Stock Targets
Per-echelon targets ↓
Nightly from Servigistics METRIC
OC Actual Position
Live stock position ↑
Every 6h back to Servigistics
🌎 Multi-State Inventory Optimisation Engine
ML demand forecasting · LP optimization solver · Service level constraints · Transfer feasibility · Dynamic state transitions
[Odoo] Odoo ERP
WH-NORTH · WH-EAST · PLT-CENT
CONNECTED
[D365] Dynamics 365
WH-SOUTH · WH-WEST
CONNECTED
Objective:
Min( WC + Stockout + Transfer Cost )
| SL ≥ 95%
🌏 Geopolitical Risk Scenario Planning
Live risk intelligence · Plant shutdowns · Shipment disruptions · AI-ranked recovery
Global Risk Index
72
↗ HIGH — Elevated since Q2
Active Disruptions
2
Kansas City · Shanghai Port
PLANT DOWN
PORT HOLD
Revenue at Risk
$306K
Plant $177K + Shipment $129K
Recovery Actions
6
AI-ranked · 2 executable now
2 READY
4 PENDING
🌍 Active Threat Feed
CRITICAL — PLT-CENT Kansas City Plant Shutdown
SKU-WELD-ROD stranded · 3 orders affected · $177K revenue at risk · Detected 2h ago
PLANT
Odoo ERP Affected
Recovery plan ready
HIGH — Shanghai Port Hold — SUP001 PO-2891
1,200 units SKU-BEAM-001 blocked · 3–6 week delay · $129K at risk · Detected 6h ago
SHIPMENT
D365 PO Flagged
Alt. supplier ready
WATCH — Taiwan Strait Tensions — SUP003 Monitor
Electronics components · 14 day buffer · Pre-emptive PO recommended
GEOPOLITICAL
Monitoring
🏭 Supplier Risk Heatmap
SUP001 Global Metals
Primary · Steel Beam
88
CRITICAL
SUP002 Reliable Resources
Approved · Multi-SKU
18
LOW
SUP003 Asian Components
Primary · Electronics
54
MEDIUM
SUP004 Pacific Supply
Approved · Valves
41
MEDIUM
SUP006 MidWest Components
Qualified · Welding
22
LOW
▶ Simulate:
📍 Disruption Impact
Click a simulation button above to begin.
⚡ Recovery Options — AI Ranked
Click a simulation button above to begin.
🏭 Alternative & Potential Suppliers
Click a simulation button above to begin.
🕐 Recovery Timeline
Click a simulation button above to begin.
🗃
IDLE
D365 F&O + BigQuery — Live Table View
Values update when disruption is simulated
🤖
Agent Live Console
5 AI Agents · Real-time event stream · Customer locations · Device connections · Servigistics signal monitor
All 5 Agents Running
1,240 Devices
SRV Sync: Active
HOU-01
DAL-02
MID-03
AUS-04
All
Connected Customer Sites
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Agent Status
5 / 5 Running
| Agent | Status | Last Action | Queue |
|---|---|---|---|
| IoT Anomaly | Active | A-001 vibration 09:42 | 3 alerts |
| Failure Prediction | Active | SIG-0881 issued 09:41 | 82% risk |
| Parts Replenishment | Active | TRF-0081 dispatched | 2 open POs |
| WO Dispatch | Active | WO-4441 → M.Johnson | 4 WOs |
| SLA Guardian | Active | WO-4441 5h 58m left | 4 clocks |
Live Device Feed — Sensor Data by Location
| Device / Asset | Site | Customer | Protocol | Sensor | Live Value | Status | Agent |
|---|---|---|---|---|---|---|---|
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Agent Decision Log — All Sites
| Time | Agent | Site | Device | Trigger | Decision | Outcome |
|---|---|---|---|---|---|---|
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Parts Replenishment Agent
Autonomous inventory management · EOQ · Croston · VMI · Bidirectional Servigistics integration
Agent Active
2 Below Safety Stock
↑↓ SRV Connected
POs Raised (30d)
34
$142K total value
Parts Fill Rate
93.4%
▲ Target 92%
Stockouts
3
Emergency POs active
Inter-Depot Moves
8
Today · 3 in transit
Stockout Cost Avoided
$340K
YTD
Avg Reorder Cycle
4.2 days
▼ vs 6.1d manual
Critical & Low Parts — Agent Action Queue
| Part / SKU | Site / Customer | On Hand | Safety Stock | ROP | In Transit | OC Rule | SRV Suggests | OC Action | Status |
|---|---|---|---|---|---|---|---|---|---|
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Forecast Explainability — What Drove Each Parts Recommendation
Croston + Neg-Binomial · IoT signal overlay · 94% accuracy
Model Accuracy — Servigistics Croston baseline vs OptiChain IoT-enhanced
Croston model alone (SRV baseline)
78%
Croston + IoT failure signal (OptiChain)
94%
16 percentage-point uplift from IoT sensor data enriching intermittent demand model. Measured over 12-month AGCO pilot, 1,240 SKUs.
Servigistics Recommendation — Croston model
SKU: NSK-6309-2RS · Site: HOU-01 · Next replenishment window: 3 days
3
Recommended qty
Demand history: 0.4 units/month (intermittent)
Service level target: 95%
Lead time: 5 days
Model: Croston / Neg-Binomial
No sensor data incorporated. Assumes historical demand pattern continues.
OptiChain Override — IoT-enriched forecast
SKU: NSK-6309-2RS · Site: HOU-01 · Pre-stage triggered immediately
8
Pre-staged qty
82% failure probability on A-001 (14–21 day RUL)
Fleet pattern: 6 similar Fendt 1050s in fleet
Cascade probability: 67% (same model, same age)
Override confidence: 91%
IoT signal overrides Croston: fleet cascade risk justifies 8 units instead of 3. Suppresses SRV PO from re-raising.
What drove the qty-8 override — factor decomposition
IoT failure signal
+4 u
A-001 primary asset demand (RUL 14–21 days)
Fleet cascade risk
+2 u
5 Fendt 1050s — 67% cascade probability in 30 days
Croston base
+3 u
SRV base recommendation retained as floor
Warranty signal
-1 u
1 unit covered by warranty; excludes from paid demand count
Final recommendation
= 8 u
Pre-staged at HOU-01 depot · Confidence: 91%
Servigistics feedback: After WO-4441 closes,
oc_actual_consumption sends qty=8 and failure_signal_triggered=true back to SRV. Croston model updates its demand history weight for intermittent vs signal-driven demand, improving the next forecast cycle.
Failure Prediction Agent
LSTM time-series anomaly detection · 91.4% accuracy · 18-day average warning lead · Bidirectional SRV signals
Agent Active
3 Assets at Elevated Risk
SIG signals sent to SRV
HOU-01MID-03All
High Risk >75%
3
Immediate action
Medium Risk 50-75%
7
Monitor closely
Model Accuracy
91.4%
Last 90 days
Avg Warning Lead
18 days
Before failure
Cost Avoided YTD
$2.1M
Unplanned downtime
Asset Risk Table — Failure Probability by Site
| Asset / Serial | Site / Machine | Customer | Component | Failure Probability | Failure Mode (LSTM) | RUL (days) | SRV Plan | OC Signal | Signal ID |
|---|---|---|---|---|---|---|---|---|---|
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AI Signal Explainability — A-001 · Fendt 1050 Vario · 82% Failure Probability
Vertex AI · LSTM + XGBoost · Confidence intervals shown
Feature Importance — What is driving the 82% prediction?
Vibration Z-axis trend (7-day slope)
38.4%
1.24g current vs 0.9g baseline · +38% over 7 days · Rate of change exceeds historical pre-failure pattern at 14 similar assets
Bearing temperature (absolute + trend)
24.1%
87°C vs 65°C baseline · Thermal and vibration correlation is a strong co-failure indicator (r=0.84 in training set)
Asset age vs design life
18.2%
A-001 is 24 months into a 36-month bearing design life · Increases prior failure probability from model baseline
Hydraulic pressure drop correlation
11.8%
Hydraulic pressure -13% coinciding with vibration rise — cross-sensor correlation adds confidence
Repair history (this asset)
7.5%
1 prior bearing replacement at 18 months · Second failure typically occurs sooner than first (learned from fleet history)
Prediction Confidence & Sensor Thresholds
Failure Probability
82%
90% confidence interval: 74% — 88%
Predicted RUL: 14–21 days · Model RMSE on test set: 2.3 days
Sensor Breach Thresholds Crossed
| Sensor | Live | Warn | Critical | State |
|---|---|---|---|---|
| Vibration Z | 1.24g | >1.0g | >1.1g | CRITICAL |
| Bearing Temp | 87°C | >80°C | >95°C | WARNING |
| Hydraulic Press. | 48 bar | <50 bar | <42 bar | WARNING |
Model trained on 14,200 bearing failure events across Fendt, MF, and Challenger fleet history (2018–2025). Servigistics pre-stage recommendation overridden from 3u → 8u based on IoT signal confidence.
Work Order Dispatch Agent
AI technician assignment · Skill match · Distance · Parts availability · <500ms decision · SRV demand feedback
Agent Active
4 Active Work Orders
First-Time Fix: 78.4%
HOU-01DAL-02MID-03AUS-04
D365 Field Service
WO Lifecycle Events
Dispatched · Arrived · Started · Closed · Labour time
✓ Microsoft native — no custom build
Field Service Mobile App
Microsoft Power Apps
GPS check-in · Parts barcode scan · Customer e-signature · WO closure
✓ Shipped with D365 — no custom build
Fuse Connect Telematics
AGCO Native Platform
Machine sensor data · Engine hours · GPS location · Fault codes
✓ AGCO pre-installed — OptiChain reads via API
OptiChain AI Layer
LTTS Build (GCP)
5 AI Agents · Servigistics integration · Dispatch optimisation · SLA guardian · IoT validation
← This is what LTTS builds and delivers
Open WOs
47
Across 4 sites
Auto-Dispatched
38
81% of all WOs
Avg MTTR
3.2 days
▼ −34% vs baseline
SLA At Risk
2
Agent escalated
Avg Skill Match
94%
vs 71% manual
1st-Time Fix Rate
78.4%
▲ +12pts vs manual
Work Order Dispatch Queue
| WO # | Asset | Site / Customer | Work Type | Technician | Skill Match | Status | SLA Clock | Parts |
|---|---|---|---|---|---|---|---|---|
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SLA Guardian Agent
Real-time SLA clock monitoring · Auto-escalation at 70% consumed · $184K penalties avoided YTD
Agent Active
All SLAs On Track
96.1% Compliance YTD
HOU-01DAL-02MID-03AUS-04
D365 Field Service
SLA Clock Source
WO open timestamp · Contract SLA terms · Customer priority tier
✓ Microsoft native — OptiChain reads via Dataverse API
Field Service Mobile
Technician Progress
Arrived · Work started · Parts used · Completed · Customer signature
✓ Microsoft Power Apps — no custom build
Fuse Connect / IoT
Post-Repair Validation
Sensor reads within 2h of WO close · Confirms repair effectiveness
✓ AGCO Fuse Connect — OptiChain validates repair outcome
SLA Guardian Agent
LTTS Build (GCP)
Real-time clock · Auto-escalation at 70/85/95% · IoT cross-validation · Penalty calculation
← OptiChain's unique SLA intelligence layer
SLA Compliance YTD
96.1%
Target ≥ 95%
Active At-Risk
2
Agent escalated
Penalty Exposure Today
$8,400
If breached now
Penalties Avoided YTD
$184K
92 escalations
Escalations Today
3
Auto-notified
Breaches YTD
4
$8,400 penalties paid
SLA Status — All Work Orders by Site
| WO # | Asset | Site / Customer | SLA | Time Remaining | Status | Escalation |
|---|---|---|---|---|---|---|
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Technician Work Progress Tracker — Live Status per WO
D365 Field Service
Mobile App GPS
IoT Post-Repair Validation
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SLA Guardian — Automatic Escalation Rules
Configured per contract tier
0–70% SLA Used
Normal
Agent monitors silently. ETA tracking via GPS. Parts status checked every 15 min.
70% SLA Used
⚠ Auto-Escalate L1
Field Supervisor notified via Teams + SMS. Agent suggests nearest available backup technician.
85% SLA Used
🚨 Auto-Escalate L2
Account Manager + Depot Manager notified. Emergency parts transfer authorised if needed.
95% SLA Used
🔴 VP + Customer Alert
VP Service + Customer contact notified. Penalty calculation prepared. All options exhausted.
How the SLA Guardian verifies work is actually complete — 4-step validation
1
D365 WO Closure
Technician closes WO in mobile app → work description, parts consumed, labour hours logged → D365 event fires → SLA clock tentatively stopped
2
Digital Sign-off
Customer digital signature captured in mobile app with GPS timestamp → attached to WO record → confirms physical presence and acceptance
3
IoT Post-Repair Check
OptiChain reads asset sensor within 2h of WO closure. Vibration, temperature, pressure must return to baseline. If still anomalous → repair flagged incomplete
4
SRV Consumption ACK
Actual parts consumed sent to Servigistics (oc_actual_consumption). SRV acknowledges → closes the loop on demand signal sent 18 days earlier
IoT Anomaly Agent
1,240 assets monitored · Vibration · Temperature · Pressure · Runtime · Real-time threshold detection
Agent Active
3 Active Alerts
MQTT + OPC-UA
Assets Online
1,842
Active Anomalies
4
Data Rate
35K+/min
Model Accuracy
94.2%
Live Sensor Anomalies
| Asset ID | Site / Location | Customer | Sensor | Current Value | Baseline | Deviation | Severity | Agent Action |
|---|---|---|---|---|---|---|---|---|
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A-001 VIBRATION
1.24g ▲
Baseline: 0.9gCRITICAL: >1.1g
A-006 PRESSURE
48 PSI ▲
Baseline: 39 PSIALERT: >45 PSI
A-009 TEMPERATURE
87°C ▲
Baseline: 76°CALERT: >85°C
A-001 HEALTH
18%
A-006 HEALTH
22%
A-009 HEALTH
29%
A-004 HEALTH
88%
IoT-based Spare Parts Prediction — Sensor Signal to Pre-Stage in <2 Minutes
Fuse Connect → LSTM → Parts Agent → Depot Action
Step 1 — Sense
Fuse Connect IoT
Sensor readings from Fendt 1050 · 30-second polling · Vibration + Temp + Hydraulic
A-001 Vib-Z: 1.24g ↑
Step 2 — Predict
LSTM Failure Model
Vertex AI model scores 14-day sensor trend · Feature importance computed · RUL estimated
82% failure · RUL 14–21d
Step 3 — Identify
Parts BOM Agent
Failure mode → parts lookup in D365 BOM · Fleet cascade analysis · Qty uplift from IoT confidence
NSK-6309-2RS × 8u
Step 4 — Stage
Pre-Stage Action
SRV safety stock override issued · D365 internal transfer raised · Depot picker notified via mobile
HOU-01 → Van-7 ✓
Step 5 — Close Loop
SRV Feedback
Actual consumption + entitlement event sent back · Croston model demand history updated · SRV PO suppressed for core return
SRV model updated ✓
Live trace — A-001 Fendt 1050 bearing event (Aug 12, 2025)
09:38:14 UTC
Fuse Connect reports Vibration Z = 1.24g (baseline 0.9g) on A-001 (FEN-1050-TX4471)
09:38:16 UTC
IoT Anomaly Agent publishes event to Cloud Pub/Sub topic
iot-anomaly-events
09:38:22 UTC
LSTM model on Vertex AI scores 14-day window → failure probability 82% · RUL 14–21 days
09:38:28 UTC
Parts BOM Agent queries D365 for A-001 bearing BOM → NSK-6309-2RS identified as primary failure part
09:38:31 UTC
Fleet cascade analysis: 5 additional Fendt 1050s at HOU-01/DAL-02 at similar age → qty uplift 3→8
09:39:04 UTC
Servigistics SRV safety stock override issued via
oc_recommended_stock · SRV confirms ACK
09:40:11 UTC
D365 internal transfer TR-2025-HOU-441 raised · HOU-01 depot → Service Van 7 · 8 × NSK-6309-2RS
Total elapsed: 1 min 57 seconds from sensor reading to parts pre-staged in van
Current IoT-driven Parts Pre-Stage Recommendations (live)
| Asset | Machine | Site | Failure Signal | Probability | RUL (days) | Parts Predicted | SRV Base Qty | OC Qty | Status |
|---|---|---|---|---|---|---|---|---|---|
| A-001 | Fendt 1050 Vario FEN-1050-TX4471 |
HOU-01 | Bearing Spalling (Vib-Z 1.24g) | 82% | 14–21 | NSK-6309-2RS | 3 | 8 | Pre-Staged ✓ |
| A-006 | MF 8S.265 MF8S-265-TX5522 |
MID-03 | Impeller Wear (pressure 48bar) | 71% | 18–28 | PRT-D001 | 2 | 4 | Transfer Pending |
| A-012 | Fendt 942 Vario FEN-942-TX4490 |
DAL-02 | Transmission bearing (temp 91°C) | 64% | 22–35 | NSK-22220-K | 1 | 3 | Monitor |
🏠 Parts BOM & Hierarchy Intelligence
Multi-level Bill of Materials · Asset → Assembly → Sub-Assembly → Part SKU · 4 sites · 1,240 active SKUs · ABC/XYZ classification
Total SKUs
1,240
4 sites monitored
Critical (A-class)
187
High cost, low volume
Stockouts Now
3
Emergency PO active
Healthy Stock
1,181
Above safety stock
Inventory Value
$2.8M
Across all depots
Fill Rate
93.4%
Target ≥ 92%
← Select a node in the BOM tree to see part details
Warranty & Entitlement Management
Contract coverage validation · Claims processing · Expiry alerts · Supplier warranty recovery · AI entitlement check
248 Active Contracts
3 Expiring in 30 days
12 Claims In Process
HOU-01
DAL-02
MID-03
All
Active Contracts
248
$12.4M total coverage value
Expiring ≤ 30 Days
3
Auto-renewal alerts sent ✓
Claims In Process
12
$84K pending supplier recovery
Claims Approved YTD
$312K
94.2% approval rate
AI Entitlement Check
<1s
Auto-checked on every WO open
Claim Denials
8
5.8% — out-of-coverage repairs
Active Warranty Contracts
| Contract # | Asset / Machine | Site | Coverage Type | Start | Expires | Status | Supplier | Coverage Value |
|---|---|---|---|---|---|---|---|---|
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Warranty Claims Pipeline
12 open
| Claim # | WO # | Asset | Failure Type | Claim Amount | Stage | Supplier |
|---|---|---|---|---|---|---|
| WCL-2025-0441 | WO-4441 | A-001 Fendt 1050 |
Bearing Spalling — manufacturing defect | $8,400 | Under Review | NSK Ltd |
| WCL-2025-0438 | WO-4433 | A-012 Fendt 942 |
Transmission bearing — within warranty period | $12,600 | Pending Docs | Fendt GmbH |
| WCL-2025-0431 | WO-4430 | A-003 Fendt 828 |
Hydraulic pump — powertrain coverage | $6,800 | Approved | AGCO Parts |
| WCL-2025-0419 | WO-4428 | A-007 MF Ideal 7 |
Header drive bearing — OEM warranty | $4,200 | Denied | AGCO Parts |
AI Entitlement Engine — Automatic Coverage Check on Every WO
Runs at WO creation · <1s response
Step 1 — Asset Lookup
Serial number queried against AGCO warranty registry and D365 contract database. Coverage type, start date, expiry retrieved in real time.
Step 2 — Coverage Match
Failure mode from IoT/technician diagnosis matched against coverage terms. Powertrain warranty covers bearing fatigue. Wear-and-tear exclusions applied automatically.
Step 3 — Claim Filed
If covered, warranty claim auto-drafted with IoT evidence (sensor readings), LSTM prediction output, and parts consumed. Sent to supplier portal for recovery.
Live example — WO-4441 entitlement check result:
Asset
A-001 · Fendt 1050 Vario
Serial
FEN-1050-TX4471
Coverage
Full Coverage
Expiry
31 Mar 2026
Failure Mode
Bearing Spalling (manufacturing defect)
Covered?
✓ YES — Full Parts + Labour
Claim Filed
WCL-2025-0441 · $8,400
Check Time
0.4s ✓
RMA & Reverse Logistics
Return Material Authorisation · Defective parts tracking · Supplier credit recovery · Core return · Closed-loop parts lifecycle
34 Open RMAs
$284K In Transit
$142K Recovered YTD
HOU-01
MID-03
All
Open RMAs
34
↑ 4 opened this week
Value In Transit
$284K
12 shipments en route to suppliers
Credit Recovered YTD
$142K
87.4% of claimed value
Avg Cycle Time
18 days
Initiation → Credit issued
Core Returns
22
Pending depot inspection
Disputed Credits
3
$18.4K under dispute with suppliers
RMA Register — Open Returns
| RMA # | Part / SKU | Asset | Site | Return Reason | Condition | Supplier | Claim Value | Stage | ETA Credit |
|---|---|---|---|---|---|---|---|---|---|
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Reverse Logistics Flow
1
RMA Initiated
AI validates warranty/defect eligibility · RMA# auto-generated · Supplier notified
34
2
Label Issued & Collected
Prepaid return label generated · Carrier collection scheduled from site
28
3
In Transit to Supplier
Tracked via carrier API · ETA monitored · Auto-alert if delayed >7 days
12
4
Supplier Inspection
Supplier confirms defect · Inspection report received · Dispute flag if rejected
8
5
Credit Issued & Closed
Credit note received · Posted to AP in D365/SAP · RMA closed
22
Supplier Credit Recovery Scorecard
| Supplier | Open RMAs | Avg Cycle | Approval Rate | Disputed | YTD Credit | Score |
|---|---|---|---|---|---|---|
| NSK Ltd | 8 | 14 days | 96% | 0 | $48K | A |
| AGCO Parts | 14 | 18 days | 91% | 2 | $64K | B+ |
| Fendt GmbH | 7 | 22 days | 84% | 1 | $22K | B |
| Massey Ferg. | 5 | 28 days | 76% | 0 | $8K | C |
Repair Order & Core Exchange
Depot repair workflow · AI Repair vs Replace scoring · Remanufacturing · Core return tracking · Cost savings vs new parts
28 Active Repair Orders
$142K Saved YTD
67% Repair Rate
HOU-01
All
Active Repair Orders
28
Avg turnaround: 4.2 days
Cost Savings YTD
$142K
Repair vs buying new parts
Repair Rate
67%
AI recommends repair (vs replace)
Cores In Process
41
Awaiting inspection or remanufacture
Cores Returned
18
Shipped back to depot stock this month
Scrap Rate
8%
Beyond economic repair threshold
Repair Order Register
AI Repair/Replace Score on every item
| RO # | Part / SKU | Asset | Site | Failure Mode | New Part Cost | Repair Cost | AI Saving | AI Decision | Status | ETA |
|---|---|---|---|---|---|---|---|---|---|---|
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AI Repair vs Replace Decision Engine
Vertex AI · XGBoost model
Decision factors (weighted)
Repair cost vs new
35%
Part age vs design life
25%
Failure severity
20%
Repair history
12%
Parts availability
8%
67%
Repair
18%
Remanufacture
7%
Replace
8%
Scrap
Core Exchange Tracker
41 cores in process
| Core ID | Part | Received From | Condition | Stage | ETA Return |
|---|---|---|---|---|---|
| COR-4441-01 | NSK-6309-2RS Bearing 45mm |
WO-4441 · HOU-01 | Worn — Repairable | In Repair | Aug 20 |
| COR-4439-01 | PRT-D001 Impeller 6" |
WO-4439 · MID-03 | Severely Worn | Awaiting Inspection | Aug 22 |
| COR-4433-01 | NSK-22220-K Spherical Roller |
WO-4433 · DAL-02 | Good — Exchange | Ready to Ship | Aug 19 ✓ |
| COR-4430-01 | PRT-P002 Hydraulic Pump |
WO-4430 · HOU-01 | BER — Scrap | Scrapped | Disposed |
Field Resources — Technicians
Federated from D365 Field Service · SAP HCM · LMS certifications · Live GPS · 247 active technicians
247 Active
7 Dispatched Today
4 Certs Expiring
D365 Field Service
247 technicians
Schedule · Active WOs · Territory
● Synced 09:41
SAP HCM
247 records
Grade · Skills · Home depot · Rate
● Synced nightly
LMS — SuccessFactors
1,482 certs
Skill certs · Expiry · Training
⚠ 4 expiring in 30 days
Mobile App GPS
Real-time
Location · Status · Last check-in
● 189 / 247 online
Saved views:
Technician Locations
189 online
Depot
Available
Dispatched
Offline
Technician Directory
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| Tech ID | Name | Home Depot | Primary Skill | Cert Status | Source | Status | Live Location |
|---|---|---|---|---|---|---|---|
| Loading technicians... | |||||||
Depot Network — Parts & Inventory
4 active depots · 1,240 SKUs · Multi-echelon inventory · Servigistics target monitoring · Live stock positions
2 Healthy
1 Stockout
2 Below Target
SRV Targets: Nightly
HOU-01 · Houston
TX-South · 312 SKUs
Fill Rate86%
TRF-0081 in progress
DAL-02 · Dallas
TX-South · 248 SKUs
Fill Rate96%
Source depot for TRF-0081/0082
MID-03 · Midland
TX-West · 180 SKUs
Fill Rate73%
TRF-0082 dispatched · ETA 2h
AUS-04 · Austin
TX-Central · 140 SKUs
Fill Rate97%
Surplus rebalance to MID-03
Saved views:
Inventory Detail — Actual vs Servigistics Target
↓ SRV nightly
↑ OC 6-hourly
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| SKU | Description | Depot | Echelon | On Hand | SRV Target | SRV ROP | In Transit | ABC | XYZ | OC Rule | Status |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Loading inventory... | |||||||||||
J&J MedTech · Mentor
Medical Device Reverse Logistics Intelligence
🔁 Implant Returns & Consignment Management
FDA UDI traceability · Consignment tray tracking · AI disposition engine · 74% structural return rate · Credit cycle automation · Regulatory-compliant workflow
💊 312 Active Consignment Trays
✓ FDA 21 CFR 820.130 Compliant
Return Rate
74.2%
Structural · consignment model
Units In Field
4,840
Across 312 hospital trays
Quarantine Queue
23
Pending QA disposition
Credits YTD
$2.8M
Auto-matched to RAs
Avg Credit Cycle
4.1 days
▼ vs 12.3d manual
Restock Rate
68%
Of returns back to field
WHY THE 70-80% RETURN RATE IS STRUCTURAL — AND HOW OPTICHAIN ADDRESSES IT
The Consignment Model Reality
●Hospital keeps full size/style range on sterile field for every case
●Surgeon selects intraoperatively — all others return unopened
●A typical tray has 8-12 units deployed per implant — 1 used
●Return is not a quality signal — it is how the model works
●Returned units may have been in OR environment — disposition required
OptiChain Agent Handles
✓Tracks every UDI in every consignment tray, at every hospital
✓Auto-raises Return Authorisation on OR completion signal
✓Disposition decision per unit: Restock / Quarantine / Destroy
✓Credit note matched and posted automatically on receipt scan
✓Tray replenishment auto-triggered to right size mix for next case
📊 Power BI Executive Cockpit
Consolidated C-suite and VP-level view · Fleet uptime · SLA · Cost per WO · Warranty recovery · LTTS delivery scorecard
Power BI Embedded
3 Role Views
Live · 15-min refresh
Fleet Uptime
96.2%
↑ 4.1pt YoY
SLA Compliance
94.8%
Target: 95%
Cost per WO
$1,840
↓ 23% vs baseline
MTTR (avg)
4.2h
↓ 34% · Target 4h
Warranty Recovery
$312K
YTD · 94% approval
OptiChain ROI
4.8×
$1.09M annual benefit
🆕 AI Self-Service Report Generator
Select data sources · Configure scope · Claude generates a combined executive narrative in real time · Download or copy
Claude Sonnet 4.6
7 Data Sources
Streaming output
🗄️
BigQuery — OptiChain
Fleet, WOs, parts, SLA, IoT events
Connected ✓
📋
D365 Field Service
Work orders, technicians, SLA contracts
Connected ✓
📦
PTC Servigistics
Demand forecast, safety stock targets
Connected ✓
📡
Fuse Connect IoT
Real-time sensor readings, anomaly events
Optional
🛡️
Warranty & Claims
Contract coverage, supplier recovery data
Optional
💰
Financial / ROI Model
Cost per WO, inventory savings, ROI data
Optional
3 sources selected