Qualixar
AI Agent Reliability Engineering
Research platform. Open source tools. Published papers.
Making AI agents trustworthy.
Products
Open source tools for AI agent reliability
7 Published Papers
Peer-reviewed research on arXiv and Zenodo
AI Agent Reliability Engineering
A new discipline at the intersection of testing, security, memory, and orchestration for AI agents. Six pillars. Seven papers. One platform.
Testing
Evaluate agent behavior with token-efficient benchmarks and adapter-based testing.
AgentAssaySecurity
Detect skill injection, prompt leakage, and unsafe tool invocations before deployment.
SkillFortifyMemory
Local-first persistent memory with Fisher-Rao geometry and semantic retrieval.
SuperLocalMemoryOrchestration
12 topologies, lifecycle management, and a universal command protocol for agents.
Qualixar OSContracts
Formal behavioral contracts — preconditions, postconditions, and invariants for agents.
AgentAssertCommunication
Peer-to-peer agent messaging, shared state, and file locking across sessions.
SLM MeshStay in the Loop
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