FRACTAL OS

Components

Fractal OS is comprised of a suite of components that uniquely combines analytics, simulation modeling, and artificial intelligence.
Click below to learn more
  • End-to-end data management with dynamic enrichment using open data
  • Off-the-shelf data, algorithms, visualizations, and other tools—plus p2p markets for collaboration
  • Powerful suites of specialty analytic services like timeseries, graphing, and microservices
  • Instant integration with powerful orchestration and automation technology to support massive scale

Analytic and Visualization Capabilities

Spatial and Temporal Analysis

Funnel Analysis & Behavioral Segmentation

Natural Language

Graph Analysis (Social and Non-Social)

Remote Sensing and Image Analysis

Custom Reports and Dashboards

  • Explore "what if" scenarios based on real-world observations or specified distributions.
  • Complete analytic and simulation-based models for better and more reliable results.
  • Support large-scale "gaming" approaches to real-world systems observation, including augmented reality.
  • Experience real-time models of businesses, processes, or systems to find and mitigate risks.

3 Types:

System Dynamics

Heavy use in technical engineering fields, but also for study of ecological or social systems.

Discrete Event

Used for decades across numerous industries and applications, including service, healthcare, finance, and defense.

Agent-Based

Traditionally academic, but increasingly adopted in enterprise settings, particularly where information about individual agents is available but interdependencies are not.

  • Reinforcement learning between every business, system, and employee.
  • Optimal scenario planning to maximize ROI and ensure business continuity.
  • Learn the "real" rules of systems and expose the best data to reduce uncertainty at least cost.
  • Find insights and take actions with the best human and machine attributes at scale.
  • Incorporate expert judgment and crowd-sourced data, blending them with empirical models.

Reinforcement Learning in Human-Machine Systems: