This company provides an AI-powered space intelligence platform for real-time satellite monitoring and collision avoidance. It utilizes advanced machine learning to analyze orbital data, predict conjunction risks, and support automated maneuver decision-making. The platform ensures sustainable orbital operations across LEO, MEO, and GEO environments.
Funding
Funding not disclosed
Founders
Product
Problem
The increasing density of active satellites and tracked debris in low, medium, and geostationary orbits creates frequent conjunction warnings that must be evaluated and acted upon quickly. Manual analysis of these warnings is labor‑intensive and cannot keep pace with the growing volume of events, leading to higher risk of collisions and operational delays. Operators therefore need an automated, high‑precision system for continuous orbital monitoring and collision avoidance.
Solution
Akilaris delivers an AI‑powered space intelligence platform that ingests live orbital data from multiple sources and provides millisecond‑level situational awareness across all orbital regimes. A multi‑agent architecture processes Two‑Line Element (TLE) data, Conjunction Data Messages (CDMs) and space‑weather inputs to generate predictive risk scores and automatically classify false alarms. The platform offers autonomous decision support, including optimal maneuver recommendations that respect fuel constraints and mission objectives. Operators can access results through secure RESTful APIs, WebSocket streams, or a web dashboard that visualizes a real‑time digital twin of the orbital environment. Continuous learning pipelines refine the underlying machine‑learning models using operator feedback, improving prediction accuracy over time. The solution complies with ISO 24113 debris‑mitigation standards and integrates with existing ground‑segment systems such as ESA’s CREAM platform.
Target Audience
The primary customers are commercial satellite operators, constellation managers, and national space agencies that require automated, high‑fidelity collision avoidance and orbital management capabilities.
Features
- Real‑time streaming of satellite telemetry and debris tracking data with sub‑second latency for LEO, MEO, and GEO zones
- Multi‑agent AI framework that parallelizes conjunction assessment, risk quantification, and maneuver optimization
- Digital twin of the orbital environment enabling what‑if scenario simulation and fuel‑efficient maneuver planning
- Automated CDM ingestion, false‑alarm filtering, and risk alert generation via RESTful API and WebSocket interfaces
- Adaptive learning pipeline that retrains models on validated events and operator feedback to reduce false positives
- Military‑grade encryption, role‑based access control, and FIPS‑compatible data storage for compliance with space‑safety regulations
- Built‑in compliance modules supporting ISO 24113 and ESA Zero‑Debris Charter requirements
- Scalable cloud infrastructure designed for quantum‑ready processing of terabytes of orbital data per day