LYNX MOSA.ic.AI®
Deterministic infrastructure for integrating AI and advanced edge workloads into mission-critical systems.
What is LYNX MOSA.ic.AI?
LYNX MOSA.ic.AI is a unified CPU and GPU software platform that enables deterministic, certifiable deployment of AI and advanced workloads in mission-critical edge systems. It brings control, performance, and lifecycle governance together, allowing AI to operate predictably within safety-critical environments without compromising certification or system integrity.
As aerospace, defense, and other regulated platforms incorporate autonomy and advanced analytics, the underlying computing architecture must support these capabilities without introducing instability, unpredictable timing behavior, or lifecycle sustainment risk.
MOSA.ic.AI provides the deployment substrate for mission AI workloads, allowing organizations to operationalize validated models inside controlled execution environments.
The platform is designed to coexist, not replace existing AI framework, allowing innovation to occur upstream while mission assurance is preserved downstream.
Product Offerings
LYNX MOSA.ic.AI combines the established safety foundations of MOSA.ic and CoreSuite into two offerings. This integration gives customers a unified safety architecture across CPU and GPU, optimized system coordination, and a clear path toward AI-enabled systems, something competitors do not currently provide in an integrated way.
MOSA.ic.AI - Graphics Edition
MOSA.ic.AI - Compute Edition
Key Benefits
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Deterministic AI Infrastructure: Deploy AI-enabled mission functions without compromising predictable platform behavior.
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Unified Mission Architecture: Support AI workloads alongside real-time, legacy, and mission management applications within a single integrated platform.
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Lifecycle Governance: Enable controlled technology refresh, workload portability, and long-term program sustainment.
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Operational Control: Maintain visibility into execution performance, resource allocation, and system partitioning across complex computing stacks.
Autonomous Airborne Refueling
Input Data:
-
External Vision
Cognition:
- Aircraft Detection / Validation
- Nozzle / Boom Tracking
Action:
- GPU Compute / Neural Network- CoPilot
- Improved Accuracy & Safety / Reduced Time
- High Confidence Model Results (Closed Data)
Single Pilot Operation
Input Data:
- External Vision
- Instrumentation Monitoring
- Radio Communication
Cognition:
- Flight Plan Validation
- Weather Patterns
- Tazi Traffic
- Runway Markers
- ATC Communication
Action:
- GPU Compute / Neural Network - CoPilot
- Smart Flightdeck / Workload Reduction
Key Benefits
Deterministic AI Infrastructure
Deploy AI-enabled mission functions without compromising predictable platform behavior.
Unified Mission Architecture
Support AI workloads alongside real-time, legacy, and mission management applications within a single integrated platform.
Lifecycle Governance
Enable controlled technology refresh, workload portability, and long-term program sustainment.
Operational Control
Maintain visibility into execution performance, resource allocation, and system partitioning across complex computing stacks.
Single Pilot Operation
Input Data:
-
External Vision
-
Instrumentation Monitoring
-
Radio Communication
Cognition:
- Flight Plan Validation
- Weather Patterns
- Tazi Traffic
- Runway Markers
- ATC Communication
Action:
- GPU Compute / NN == CoPilot
- Smart Flightdeck / Workload Reduction
Autonomous Airborne Refueling
Input Data:
-
External Vision
Cognition:
- Aircraft Detection / Validation
- Nozzle / Boom Tracking
Action:
- GPU Compute / NN == CoPilot
- Improved Accuracy & Safety / Reduced Time
- High Confidence Model Results (Closed Data)
