IoT Data Anomaly Detection

Concentio® IoT Data Anomaly Detection by Scry AI is an Enterprise AI application empowered by AI algorithms trained in analyzing over 10 million data points simultaneously across an IoT network to predict imminent failure risks.

Key Features

  • Prebuilt APIs to source and map and process Financial Statements from several internal and external sources.
  • Highly configurable - create custom templates for capturing, spreading, reporting and projecting financial statement data.
  • High availability and scalability in the enterprise application segment. Data is stored in a centralized database for data analysis and reporting requirements.
  • Pre-built financial ontologies & business rules that are dynamically updated to improve the product accuracy over time.

Use Cases

  • Reconcile weekly, monthly, and yearly NAV estimates.
  • Reconcile fee calculation and calculation of fee waterfall.
  • Verify and reconcile price calculations.
  • Reconcile contract notes and trade confirmations.
  • Reconcile treasury transactions.
  • Reconcile investor fee and liquidity terms.
  • Reconcile trade and cash positions.
  • Automated online reporting.
  • Reconcile balance sheets, income statements, cash-flow statements, changes in equity.

IoT Data Anomaly Detection Success Statistics

  • IoT Data Anomaly Detection Success Statistics

    Concentio® IoT Data Anomaly Detection features a robust feature suite that addresses the core challenges of IoT data anomaly detection utilizing features such as:

    • 90%+ Accuracy from the time of integration from 25+ pre-trained proprietary AI algorithms.
    • 10 Million+ Variables accommodated simultaneously across devices and networks.
    • A complete User focused graphical interface design.
    • 100% Customizable graphs and templates for data analysis, visualization and reporting.
  • IoT Data Anomaly Detection Features
    • 25+ proprietary AI based algorithms.
    • Can simultaneously accommodate more than ten million variables (i.e., devices and sensors).
    • Real time validation against system generated device fingerprint of each device and sensor.
    • Noise detection and reduction using specific filters.
    • Time-series, and frequency domain analyses.
    • Real time alerts related to anomalies.
    • Reinforcement learning via human intelligence & machine learning improves the accuracy of underlying algorithms.

Concentio® IoT Data Anomaly Detection serves industries such as

  • HealthTech
  • Construction
  • Industrial Plants & Equipments Firms
  • City Services
  • Utilities
  • Mobility

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