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In developmentTRL 4v0.x

MaxQai

AI Autonomous Control & Safety Authority

A three-layer autonomous control system designed for safety-critical space infrastructure. Layer 0 runs a deterministic Rust control loop. Layer 1 provides adaptive decision-making for mission planning and resource optimization. Layer 2 uses large language models for crew interaction, anomaly interpretation, and natural-language reporting — with domain-specific control agents across every operational subsystem. The eye is the iPad application crew and operators interact with MaxQai through: tap the eye to start the mic, the iris pulses and glows with the conversation, and voice in and out flows through Max, the eye’s voice modality.

MaxQai brand mark

TRL 4

Technology Readiness

Capabilities

L0: Deterministic Rust control loop
L1: Adaptive decision engine
L2: LLM-based crew interaction and anomaly interpretation
Domain-specific control agents across every operational subsystem
The eye — the iPad app for visual focus, pulsing-iris feedback, and voice interaction
Max — voice in and out, one modality inside the eye
Fault detection, isolation, and recovery (FDIR)
Multi-vehicle coordination protocols

Target Markets

  • Space station operators requiring autonomous control
  • Spacecraft manufacturers integrating AI safety systems
  • Defense and government autonomous systems programs
  • Critical infrastructure operators

Technology

RustPythonLLM integration layerWebSocket real-time telemetryiPad (SwiftUI)

How MaxQai Fits the Platform

The autonomy layer for the entire sTARS platform — the Operate pillar. Controls magnetosphere coil operations, manages Spine subsystems, and runs under Spine-Sim supervision for hardware-in-the-loop testing before deployment.

Interested in MaxQai?

Get in touch to learn more about how MaxQai fits your needs.

See the Architecture
Spine-SimSpace Lease