Every Gram Accounted For.
Every Fraud Detected.
ProfitGuard is the first and only platform to bring ML-powered tare weight fraud detection directly into SAP S/4HANA logistics. Our hybrid AI ensemble catches weight manipulation schemes with 99.1% accuracy — protecting millions in material costs across your supply chain.
The Silent Drain on Your Supply Chain
Weight-based fraud is one of the most underdetected forms of supply chain theft. Carriers and suppliers manipulate tare weights, gross weights, and shipment quantities — often for months or years before discovery.
estimated annual weight-based fraud globally
According to industry supply chain integrity reports
average time before manual detection
ProfitGuard detects in real time
of material costs lost to weight manipulation
For companies with $500M+ logistics spend
Why traditional controls fail:
Manual spot checks only audit 2-5% of shipments. Scale reports are reviewed weekly or monthly. Gradual manipulation stays within tolerance bands. Collusion between carriers and receivers bypasses approval workflows. ProfitGuard eliminates all of these blind spots with AI that analyzes 100% of weight transactions in real time.
Four ML Models. One Verdict.
Each model brings a different detection strength. Combined, they achieve 99.1% accuracy with less than 3% false positives — the highest precision weight fraud detection available in any ERP platform.
Isolation Forest Anomaly Detection
Unsupervised ML model that identifies weight entries significantly deviating from expected patterns — catching subtle manipulation that manual checks miss.
How it works: Analyzes historical weight distributions per material, carrier, and route to establish baselines. Flags entries beyond 2.5 standard deviations with context-aware thresholds.
LSTM Temporal Pattern Analysis
Deep learning model that analyzes weight sequences over time — detecting gradual manipulation schemes where small variances accumulate into significant fraud.
How it works: Processes 90-day rolling windows of weight data per carrier-route combination. Detects trending drift, periodic manipulation, and seasonal pattern breaks.
Zynoviq Gradient Booster
Supervised classification model trained on confirmed fraud cases. Combines 47 features including weight, time, carrier history, and material properties for precise fraud scoring.
How it works: Uses 47 engineered features across weight variance, carrier behavior, material density, route distance, and temporal patterns. Human-feedback loop for continuous improvement.
Hybrid Ensemble Detection
Combines all three models into a weighted ensemble that maximizes detection while minimizing false positives — achieving the best of statistical, temporal, and supervised methods.
How it works: Weighted voting across Anomaly Detection (30%), Pattern Analysis (25%), and Gradient Booster (45%). Confidence calibration ensures <3% false positive rate at 99.1% true detection.
Six Weight Fraud Schemes We Detect
Every scheme our AI has identified and prevented in production deployments across manufacturing, mining, logistics, and commodity trading enterprises.
Tare Weight Over-Reporting
$450K-$2.1M annuallyCarriers inflate the empty vehicle weight (tare) so net weight appears lower, allowing them to charge for goods never delivered.
Detection: Historical tare comparison per vehicle ID + route-adjusted density analysis
Gross Weight Under-Reporting
$380K-$1.8M annuallySuppliers report lower gross weight to reduce material costs while shipping less product than invoiced.
Detection: Expected weight calculation from material volume + density cross-reference
Phantom Shipment Weights
$250K-$1.2M annuallyFabricated weight entries for shipments that never occurred or contained different materials than documented.
Detection: Cross-reference with GR timestamps, badge data, and carrier GPS telemetry
Gradual Weight Drift
$200K-$900K annuallySophisticated scheme where weight manipulation increases incrementally over months — staying within normal variance but accumulating significant theft.
Detection: LSTM temporal trend analysis with 90-day rolling window drift detection
Scale Calibration Exploitation
$150K-$600K annuallyManipulation of scale calibration schedules or settings to introduce systematic measurement errors that benefit specific carriers or suppliers.
Detection: Cross-scale correlation analysis + calibration drift monitoring per facility
Carrier-Supplier Collusion
$500K-$3.2M annuallyCoordinated fraud between carriers and receiving personnel to accept underweight deliveries as full-weight with forged documentation.
Detection: Behavioral analytics on receiver-carrier pair patterns + approval timing anomalies
Deep SAP S/4HANA Logistics Integration
ProfitGuard connects directly to SAP S/4HANA logistics modules via OData and RFC — capturing weight data at the point of entry and analyzing it before goods receipt is confirmed.
Auto-Training Pipeline
ProfitGuard continuously improves through a self-learning pipeline that incorporates new fraud patterns and operator feedback.
Stop Losing Millions to Weight Fraud
If your organization processes weight-based transactions in SAP, ProfitGuard will find fraud you did not know existed. 99.1% accuracy. Real-time detection. Proven at scale.
Free trial • Connects to SAP in hours • 99.1% detection accuracy • ROI guarantee