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Self-Healing Agents - Autonomous System Resilience (MVP)

MVP

November 10, 2025

MVP operational • Internal deployment • Governance research ongoing

AI systems degrade over time due to data drift, environment changes, and unforeseen interactions. Neuralyn Labs explored self-healing agents capable of detecting and correcting failures autonomously.

Context

AI systems degrade over time due to data drift, environment changes, and unforeseen interactions. Neuralyn Labs explored self-healing agents capable of detecting and correcting failures autonomously.

Objective

  • •Monitor its own behavior
  • •Detect anomalies or degradation
  • •Initiate corrective actions within defined constraints

System Deployed

  • •Self-Healing Agent Framework (MVP)
  • •Telemetry-driven monitoring
  • •Rule-bounded autonomous repair loops
  • •Human override safeguards

Environment

  • •Long-running internal services
  • •Simulated failure injection
  • •Controlled rollback mechanisms

Observations

  • •Early detection reduced downtime significantly
  • •Autonomous correction worked best within strict guardrails
  • •Governance constraints are essential to prevent over-correction

Key Insight

Self-healing AI is viable only when ethics and control are embedded by design.

Research Transparency Notice

All case studies represent research pilots, internal experiments, prototype deployments, or simulated environments. Neuralyn Labs does not claim clinical efficacy, diagnostic capability, or therapeutic outcomes unless explicitly stated under approved clinical protocols.