Industrial IQ | AI2COE | InventoryMind AI
InventoryMind AI Inventory Risk Report
45.8Inventory health score
Material RiskRisk level
Medium ConfidenceConfidence
21Evidence records
Source mode: Sample dataset result. Sample results demonstrate workflow and report structure; uploaded-data results replace assumptions with customer source evidence.
Score interpretation: Lower health or readiness scores indicate higher unresolved exposure, weaker readiness, or stronger review need. Scores are deterministic and derived from mapped source fields, findings, evidence, and component inputs.
Executive interpretation: Focus on asset integrity, turnaround readiness, working capital exposure, and audit-safe ERP preparation.
Report delivery and governance controls
Email
Report email path
Authenticated Industrial IQ runs attempt branded report email delivery and retain delivery status in the platform report inventory.
Review
Human review required
Low-confidence or high-impact findings should be accepted, rejected, assigned, deferred, or marked needs-more-data before remediation.
ERP safety
No ERP write-back
Industrial IQ produces evidence and recommendations only. It does not autonomously change SAP, Maximo, Oracle, EAM, CMMS, procurement, inventory, or asset records.
CFO command view
194045.0Capital exposure signal
23285.4-54332.6Recoverable range
34928.1Annual leakage signal
Material RiskBoard attention band
Diagnostic components
154200.0INVENTORY VALUE
4DEAD STOCK ROWS
5SLOW MOVING ROWS
4EXCESS ROWS
0STOCKOUT ROWS
33924.0CARRYING COST ESTIMATE
12336.0DUPLICATE STOCK EXPOSURE
active_deterministic_evidence_engineDIAGNOSTIC DEPTH
Score formula: 100 - risk_rows/source_rows*100 where stockout rows are weighted double Random score used: False
| Score input | Value |
|---|---|
| inventory value | 154200.0 |
| dead stock rows | 4 |
| slow moving rows | 5 |
| excess rows | 4 |
| stockout rows | 0 |
| carrying cost estimate | 33924.0 |
| duplicate stock exposure | 12336.0 |
| required fields mapped | 2 |
| optional fields mapped | 11 |
| source rows profiled | 24 |
| estimated row value total | 154200.0 |
| critical understock rows | 0 |
| minmax policy gap rows | 0 |
| high value immobile rows | 0 |
| duplicate inventory families | 1 |
| duplicate inventory family value | 154200.0 |
Product maturity and competitive depth
Competitive position: Competes with Verusen-style MRO optimization by making every recommendation source-backed, confidence-tiered, and reviewable before action.
| Priority | Implemented product capability |
|---|---|
| P0 | Dead stock, slow-moving stock, excess inventory, stockout risk, critical spare coverage, and duplicate stock exposure.; Min/max exception detection and transfer-before-purchase evidence.; Carrying-cost estimate with sample-vs-uploaded-data labeling. |
| P1 | ABC/XYZ segmentation, site transfer candidates, inventory policy exceptions, and critical understock queue.; Inventory health trend by site, value band, criticality, and duplicate-family exposure.; Executive interpretation for CFO, COO, inventory, procurement, and maintenance. |
| P2 | Service-level scenario simulator with stock-reduction, stockout-risk, and critical-spare protection assumptions.; Monthly inventory optimization review with prior-run comparison and renewal value report.; Benchmark comparison by industry, site type, and critical spare class. |
ICP packaging
| Package | Engines | Decision supported |
|---|---|---|
| CFO Pack | FinanceMind AI, PartsCleanse AI, InventoryMind AI, ProcureMind AI | Fund value realization only after capital exposure, carrying cost, procurement leakage, and review confidence are visible. |
| COO Pack | ReliabilityMind AI, AssetMind AI, InventoryMind AI | Prioritize site readiness, asset coverage, false stockout risk, and operational action queues. |
| Procurement Pack | ProcureMind AI, PartsCleanse AI, InventoryMind AI, FinanceMind AI | Convert supplier, PO, duplicate stock, and price-variance evidence into sourcing action without unsupported savings claims. |
Advanced product insights
| Product output | Diagnostic value |
|---|---|
| abc xyz model | {"A_value_sites": 3, "B_value_sites": 1, "C_value_sites": 0, "X_stable_demand_signal": 24, "Y_review_demand_signal": 0, "Z_stockout_or_erratic_signal": 0} |
| transfer before purchase | [{"candidate_value": 51450.0, "from_site": "Plant-4", "recommendation": "Review transfer before purchase where another site has excess or immobile value."}, {"candidate_value": 39600.0, "from_site": "Plant-3", "recommendation": "Review transfer before purchase where another site has excess or immobile value."}, {"candidate_value": 36750.0, "from_site": "Plant-2", "recommendation": "Review transfer before purchase where another site has excess or immobile value."}, {"candidate_value": 26400.0, "from_site": "Plant-1", "recommendation": "Review transfer before purchase where another site has excess or immobile value."}] |
| policy exceptions | {"critical_understock_rows": 0, "minmax_policy_gap_rows": 0} |
| service level scenario | {"base_stock_reduction_assumption": "12% of reviewed non-critical excess and duplicate-stock exposure", "conservative_stock_reduction_assumption": "5% of non-critical excess and immobile value after review", "protect_critical_spares": true, "risk_control": "Do not reduce critical or shutdown spares without maintenance approval."} |
Buyer committee views
CFO
Can quantified exposure justify a diagnostic or remediation budget?
InventoryMind AI shows 194045.0 as the current capital or leakage signal before owner review.
Next question: Which findings have enough confidence and value to enter the financial business case?
COO
Which findings threaten operational continuity, site readiness, or uptime?
1 high-attention findings require operational owner review.
Next question: Which findings must be resolved before the next outage, shutdown, or planning cycle?
CIO
Is the data ready for governed AI without ERP write-back risk?
Industrial IQ produced evidence from exports only and did not change ERP, EAM, CMMS, or procurement systems.
Next question: Which missing fields or governance gaps should be fixed in the next export?
Procurement
Where do supplier, purchase, or stocked-but-purchased signals need review?
Procurement actions should be evidence-led and routed through human review before supplier action.
Next question: Which supplier or purchase findings are defensible enough for category review?
Maintenance
Will spare availability and catalog quality support maintenance execution?
Maintenance should use the evidence queue to protect planned work and critical assets.
Next question: Which findings block planned work, shutdown readiness, or critical equipment coverage?
Board
Is this risk material enough to fund recurring diagnostic intelligence?
The result is diagnostic evidence, not an autonomous system change or unsupported ROI claim.
Next question: Should leadership fund the next diagnostic cycle, review queue, or remediation scope?
Evidence graph
Model: Source Record -> Finding -> Evidence -> Confidence -> Business Impact -> Recommended Action -> Review Status -> Report -> Score History
28 nodes | 27 evidence relationships. This graph links uploaded source rows to findings, confidence, business impact, recommended actions, report output, and score history.
Renewal value view
194045.0EXPOSURE IDENTIFIED
5REVIEW QUEUE SIZE
5ACTIONS CREATED
0ACTIONS REVIEWED
15523.6CONSERVATIVE VALUE REALIZATION
31047.2BASE VALUE REALIZATION
monthly for high-risk sites; quarterly for controlled sitesNEXT REVIEW CADENCE
Recurring value interpretation: Compare this run against the next upload to show exposure reviewed, actions completed, score movement, and remaining risk.
Findings
Trust control: Each finding must be interpreted with its confidence, evidence count, mapped fields, and source records. Similar-looking industrial records may still require owner review before action.
| Analyzer | Finding | Severity | Confidence | Evidence | Action |
|---|---|---|---|---|---|
| Dead Stock Detector | 4 rows indicate dead or inactive stock | HIGH | 86% | 4 | Review for disposal, transfer, or engineering validation. |
| Slow-Moving Inventory Analyzer | 5 rows indicate slow-moving stock | MEDIUM | 74% | 5 | Review stocking policy and reclassify long-tail inventory. |
| Excess Inventory Analyzer | 4 rows indicate excess inventory | MEDIUM | 74% | 4 | Reset min/max policy and release surplus working capital. |
| Duplicate Stock Exposure Analyzer | Duplicated stock exposure signal detected from repeated catalog signatures | MEDIUM | 68% | 1 | Run PartsCleanse AI and reconcile duplicate stock before procurement or disposal decisions. |
| Data Completeness Gate | 2 mapped fields need stronger coverage before recurring automation | MEDIUM | 68% | 8 | Improve field coverage or keep affected findings in human review until the next upload cycle. |
Evidence records
| ID | Confidence tier | Severity | Description | Value | Source | Reason codes |
|---|---|---|---|---|---|---|
| E-d628a7a5 | High Confidence | HIGH | 4 rows indicate dead or inactive stock | 10325.0 | row:5:MAT-005-005 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-7be6ef78 | High Confidence | HIGH | 4 rows indicate dead or inactive stock | 5400.0 | row:10:MAT-004-010 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-6778ba9b | High Confidence | HIGH | 4 rows indicate dead or inactive stock | 11025.0 | row:15:MAT-003-015 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-238a80ab | High Confidence | HIGH | 4 rows indicate dead or inactive stock | 6600.0 | row:20:MAT-002-020 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-64eecd97 | Medium Confidence | MEDIUM | 5 rows indicate slow-moving stock | 2925.0 | row:1:MAT-001-001 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-0b445044 | Medium Confidence | MEDIUM | 5 rows indicate slow-moving stock | 6800.0 | row:6:MAT-000-006 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-8b1aa588 | Medium Confidence | MEDIUM | 5 rows indicate slow-moving stock | 7375.0 | row:11:MAT-005-011 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-1e6dd299 | Medium Confidence | MEDIUM | 5 rows indicate slow-moving stock | 2700.0 | row:16:MAT-004-016 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-226331f7 | Medium Confidence | MEDIUM | 5 rows indicate slow-moving stock | 8575.0 | row:21:MAT-003-021 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-22d1affc | Medium Confidence | MEDIUM | 4 rows indicate excess inventory | 6800.0 | row:6:MAT-000-006 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-9107214b | Medium Confidence | MEDIUM | 4 rows indicate excess inventory | 8775.0 | row:7:MAT-001-007 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-58107e09 | Medium Confidence | MEDIUM | 4 rows indicate excess inventory | 7375.0 | row:11:MAT-005-011 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-1dab32c5 | Medium Confidence | MEDIUM | 4 rows indicate excess inventory | 8575.0 | row:21:MAT-003-021 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-ffbd1940 | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 2925.0 | row:1:MAT-001-001 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-1b20b7c1 | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 4400.0 | row:2:MAT-002-002 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-7698f896 | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 6125.0 | row:3:MAT-003-003 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-c808c031 | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 8100.0 | row:4:MAT-004-004 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-187ab9b4 | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 10325.0 | row:5:MAT-005-005 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-34b54370 | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 6800.0 | row:6:MAT-000-006 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-a2349a16 | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 8775.0 | row:7:MAT-001-007 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
| E-b829872e | Medium Confidence | MEDIUM | 2 mapped fields need stronger coverage before recurring automation | 2200.0 | row:8:MAT-002-008 | material-id-present, description-signature, site-context, value-bearing-row, spec-token-match |
Recommended actions
P1
Improve field coverage or keep affected findings in human review until the next upload cycle.
Owner: CFO | Due: 60 days
P0
Review for disposal, transfer, or engineering validation.
Owner: CFO | Due: 30 days
P1
Reset min/max policy and release surplus working capital.
Owner: CFO | Due: 60 days
P1
Review stocking policy and reclassify long-tail inventory.
Owner: CFO | Due: 60 days
P1
Run PartsCleanse AI and reconcile duplicate stock before procurement or disposal decisions.
Owner: CFO | Due: 60 days
Mapping and validation
| Input | Source column | Completeness | Confidence | Reason |
|---|---|---|---|---|
| material_id | material_id | % | % | |
| quantity | quantity | % | % | |
| description | description | % | % | |
| unit_cost | unit_cost | % | % | |
| stock_value | stock_value | % | % | |
| last_movement_date | last_movement_date | % | % | |
| movement_qty | movement_qty | % | % | |
| demand | demand | % | % | |
| criticality | criticality | % | % | |
| min_stock | min_stock | % | % | |
| max_stock | max_stock | % | % | |
| site | site | % | % | |
| currency | currency | % | % |
Source fit, AI match, and normalization
100%Source fit score
100.0%AI match score
100%Mapping readiness score
94.3%Diagnostic confidence score
Workbench interpretation: Source fit measures whether the uploaded file contains recognizable inputs. AI match measures column-mapping confidence. Diagnostic readiness measures whether the normalized mapped data can support trustworthy engine output.
| Quality signal | Value |
|---|---|
| source fit score | 100 |
| ai match score | 100.0 |
| diagnostic readiness score | 100 |
| required mapped | 2 |
| required total | 2 |
| optional mapped | 11 |
| optional total | 11 |
| required completeness | 100.0 |
| row count | 24 |
| column count | 34 |
| blockers | 0 |
| warnings | 0 |
| source fit band | Strong |
| ai match band | Strong |
| readiness band | Strong |
| diagnostic confidence score | 94.3 |
| diagnostic confidence band | Strong |
Normalization plan
| Engine field | Source column | Original sample | Normalized preview | Rule |
|---|---|---|---|---|
| Material Id | material_id | MAT-001-001 | MAT-001-001 | Trim whitespace, preserve leading zeroes, normalize item/material identifiers, and keep original source reference. |
| Quantity | quantity | 3 | 3 | Parse numeric quantity, keep negatives for audit context, and separate blank/zero from missing. |
| Description | description | Oil & Gas pump bearing seal kit model 1 stainless 4 inch | OIL & GAS PUMP BEARING SEAL KIT MODEL 1 STAINLESS 4 INCH | Normalize case, abbreviations, punctuation, industrial units, specification tokens, and obvious spacing noise. |
| Unit Cost | unit_cost | 975 | 975 | Parse unit cost, retain source currency, and separate uploaded value from benchmark assumption. |
| Stock Value | stock_value | 2925 | 2925 | Parse extended value, apply currency context where available, and label missing valuation. |
| Last Movement Date | last_movement_date | Missing | Missing | Parse date-like values into movement age bands for inventory risk. |
| Movement Qty | movement_qty | 1 | 1 | Normalize blanks, trim source values, preserve original evidence, and label any assumptions before engine execution. |
| Demand | demand | Missing | Missing | Normalize blanks, trim source values, preserve original evidence, and label any assumptions before engine execution. |
| Criticality | criticality | Medium | MEDIUM | Normalize High/Medium/Low, shutdown, safety, AOG, and critical-spare signals. |
| Min Stock | min_stock | 2 | 2 | Normalize blanks, trim source values, preserve original evidence, and label any assumptions before engine execution. |
| Max Stock | max_stock | 12 | 12 | Normalize blanks, trim source values, preserve original evidence, and label any assumptions before engine execution. |
| Site | site | Plant-2 | Plant-2 | Normalize plant, site, storeroom, facility, depot, or operating-unit labels. |
| Currency | currency | USD | USD | Normalize ISO currency code or use country/system assumption with visible limitation. |
Assumptions and limitations
Assumptions
- Uploaded data is treated as the source of truth for this diagnostic run.
- No ERP write-back is performed. Outputs are recommendations and evidence records only.
- Financial estimates use uploaded values where available and conservative assumptions otherwise.
- Industry language is adjusted for Oil & Gas: plants, wells, refineries, shutdowns, turnarounds, and asset integrity.
- Workbench scores were calculated before and after engine execution: source fit 100%, AI match 100.0%, mapping readiness 100%, diagnostic confidence 94.3%.
- Public sample report: deterministic AI2COE sample data was used. Replace with uploaded customer data for customer-specific findings.
Limitations
- Results are diagnostic signals, not final accounting entries.
- Low-confidence findings require human review before remediation.
- Missing source fields reduce confidence and may suppress some analyzers.
- Benchmarks are labelled assumptions unless validated by uploaded data.