7 papers published on arXiv

Qualixar

AI Agent Reliability Engineering

Research platform. Open source tools. Published papers.
Making AI agents trustworthy.

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Academic Citations

7 Published Papers

Peer-reviewed research on arXiv and Zenodo

2026

Qualixar OS: A Universal Operating System for AI Agent Orchestration

arXiv:2604.06392
2026

SuperLocalMemory V3.3: The Living Brain — Cognitive Memory for AI Agents

arXiv:2604.04514
2026

SuperLocalMemory V3: Information-Geometric Agent Memory

arXiv:2603.14588
2026

AgentAssay: Token-Efficient Agent Evaluation via Stochastic Verdicts

arXiv:2603.02601
2026

SkillFortify: Securing the AI Agent Skill Supply Chain

arXiv:2603.00195
2025

AgentAssert: Behavioral Contracts for AI Agent Compliance

arXiv:2602.22302
2026

SuperLocalMemory V2: Privacy-Preserving Multi-Agent Memory

arXiv:2603.02240

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.

01

Testing

Evaluate agent behavior with token-efficient benchmarks and adapter-based testing.

AgentAssay
02

Security

Detect skill injection, prompt leakage, and unsafe tool invocations before deployment.

SkillFortify
03

Memory

Local-first persistent memory with Fisher-Rao geometry and semantic retrieval.

SuperLocalMemory
04

Orchestration

12 topologies, lifecycle management, and a universal command protocol for agents.

Qualixar OS
05

Contracts

Formal behavioral contracts — preconditions, postconditions, and invariants for agents.

AgentAssert
06

Communication

Peer-to-peer agent messaging, shared state, and file locking across sessions.

SLM Mesh

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