Distributed Intelligence

Superior results with real world data.

Distributed Intelligence

Superior results with real world data.

Distributed Intelligence

Superior results with real world data.

Overview

At AxonAI, we overcome the limitations of centralized analytics systems by deploying swarms of simple, massively paralleled relational and behavioral intelligence modules. These modules are highly configurable and can be used to detect patterns and predict outcomes in large data sets that are heterogeneous, incomplete, and dynamically changing.

RELATIONAL

INTELLIGENCE

AxonAI products in the relational family support knowledge extraction from complex dynamic data for enhanced situational awareness in an ongoing human-machine collaboration in a wide range of application domains.

BEHAVIORAL

INTELLIGENCE

AxonAI products in the behavioral family provide continuously updated risk profiles for broad classes of events based on multi-faceted real-time data. The underlying causal domain models learn from observations and human operator guidance.

RELATIONAL

INTELLIGENCE

AxonAI products in the relational family support knowledge extraction from complex dynamic data for enhanced situational awareness in an ongoing human-machine collaboration in a wide range of application domains.

BEHAVIORAL

INTELLIGENCE

AxonAI products in the behavioral family provide continuously updated risk profiles for broad classes of events based on multi-faceted real-time data. The underlying causal domain models learn from observations and human operator guidance.

Advantages

Distributed

Optimized for distributed, heterogeneous, incomplete, and ever-changing real world data:

  • Simple relational and behavioral rules make human interaction and configuration clear
  • Distributed architecture drives speed of resolution, removes infrastructure scale limitations

Configurable

Utilizes multi-variate relational and behavioral models to detect and forecast:

  • Relational rules range from pre-configured self-weighting to feedback auto-weighting
  • Behavioral rules range from social, operational, financial, geographic, and more
  • Generates detailed confidence level for results

Dynamic

Constantly runs in the background, processing new information and converging on results:

  • New data creates localized changes which propagate through the system to affect results
  • Snapshots of results can be taken at any time
  • Leverages machine learning feedback to continuously improve results