NeuroCert: Certifying Autonomy with Confidence
From AI Autonomy to Assured Certification
NeuroCert brings traceability, explainability, and formal assurance to AI-driven space autonomy. Designed for mission-critical environments, NeuroCert transforms black-box AI systems into certifiable, transparent components using a modular certification framework. By integrating trace logging, constraint monitoring, interpretability layers, and adaptive validation logic, NeuroCert enables scalable, risk-aware certification for autonomous systems operating beyond Earth.
The result is a certification architecture that supports human oversight, mission compliance, and continuous assurance—even as AI systems adapt and evolve across deep space conditions.
Core Modules
- Trace Logging Module: Captures AI execution paths and decision timelines to support reproducibility and post-mission forensics.
- Constraint Monitoring Layer: Uses formal methods and real-time checks to flag deviations from verified operational bounds.
- Interpretability Scaffold: Generates human-readable explanations (e.g., via LIME/SHAP) for opaque model behaviors.
- Adaptive Certification Logic: Adjusts V&V rigor dynamically based on AI model updates, confidence levels, or mission risk profiles.
- Agent Instrumentation Hooks: Allows developers to embed certification-aware callbacks into deployed autonomy stacks.
NeuroCert’s Differentiation
Traceable Autonomy Engineering
NeuroCert embeds transparency and traceability into the heart of autonomy. Our modular AI certification stack combines formal methods, symbolic telemetry, and runtime observability to produce autonomy that can be verified, explained, and trusted. Each AI action is logged, monitored, and validated in real-time or in simulation.
Mission-Critical Constraint Monitoring
We deploy constraint enforcement modules that perform formal, symbolic checks across safety, timing, and mission logic boundaries. Unlike black-box verifiers, NeuroCert ensures constraint violations are flagged with context, whether during simulation or in-flight execution.
Adaptive Certification Logic
AI changes.....so should certification. NeuroCert adapts its testing and validation pathways as autonomy models evolve, mission conditions shift, or new risk thresholds are introduced. This makes the system ideal for long-term deployment and high-change operational theaters like space autonomy.
Human-Auditable Explainability
NeuroCert generates explainable, human-readable reports using tools like SHAP, LIME, and symbolic interpretability layers. These artifacts allow regulators, engineers, and mission assurance personnel to understand what the AI did, why it did it, and whether it was safe.
Digital Twin Integration for Validation
We integrate with high-fidelity digital twins to enable continuous testing of AI decision logic under realistic space mission conditions, like latency, radiation, or sensor degradation. These simulated testbeds generate the evidence base required for certification readiness.
Defense-Aligned Readiness
Our development stack is designed with defense needs in mind—containerized, air-gapped, and standards-aware. NeuroCert can integrate with existing software assurance workflows, model-based systems engineering pipelines, and NASA validation frameworks.