O Analytics

Overview

Problem: Limited real-time capability to detect, classify and monitor not-before-seen space objects.

Solution: Patent-pending detection and characterization algorithms as part of a comprehensive Space Object Custody Management System (SOCMS). Field Validation: Pre-field

Technology Maturity (TRL): 6 | Components tested on real world sensor datasets.

Strategic Advantage: Patent-pending image processing code enables precision (i.e., accurate) real-time (i.e., fast) performance and low bandwidth required results (i.e., efficient) autonomously (i.e., AI/ML-enabled) from the edge (i.e., space- or ground-based).

Go-to-Market Access: Primarily AFWERX.

Dual-Use Potential: SOCMS can be extended to sovereign ally countries and commercial satellite constellation operators.

Team: Our team is led by an award-winning computational scientist with extensive experience in defense systems sensors, signal and image processing, AI/ML and technology management. Our exceptional team of computer science, physics, machine learning, sensor phenomenology, data science, space intelligence and non-Earth imagery (NEI) experts include a number of patent holders (i.e., innovators), and have 40+ combined years of defense, commercial aerospace, and government R&D experience.

Competitive Landscape: ExoAnalytics, Slingshot Aerospace, Kratos, LeoLabs and others offering a single sensor phenomenology are hardware dependent/limited. Our solution is sensor agnostic and fuses space object data from multiples sensor sources in real-time.

Primary User: Space Systems Command and combatant commands.

User-Critical Problem: The ultimate pain point is the unacceptable likelihood that a bad actor (i.e., missile) could penetrate space without detection and consequently, without adequate time to respond.