# AI Engine — Pattern Detection That Scales

Human reviewers miss things. Our AI anomaly detection engine acts as the first responder — scanning data for signs of manipulation, duplication, inconsistency, or synthetic tampering.



### Training Methodology:

The model is trained on a mixture of public datasets, synthetic falsified datasets, and industry-specific corpora (e.g., financial records, medical logs). It uses unsupervised learning to identify outliers, and supervised methods to classify known manipulation patterns.



### What It Detects:

* Anomalous values and statistical inconsistencies
* Temporal sequence drift (e.g., fabricated timestamps)
* Duplicate blocks or repeated phrases (plagiarism or fraud)
* AI-generated text signatures or synthetic data traits\


Each document or dataset is assigned a fraud risk score and a list of flagged areas. This feeds directly into the anonymized final report.

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