AI
Reliability
Engineering
Qualixar is the research laboratory defining the specifications, constraints, and runtime meshes for autonomous intelligence networks.
The Qualixar Arsenal
Eight production-ready developer tools built for structural AI Reliability Engineering.
SuperLocalMemory (SLM)
Local-first agent memory adapter using contextual semantic hooks to persist entities, decisions, and system profiles across concurrent loops without data leakage.
Qualixar OS (QOS)
An agent-native runtime operating system optimizing resource partitioning and model calls.
AgentAssert
Express state and behavioral assertions for model output streams. Fails execution loops immediately when safety guards are violated.
AgentAssay
A framework to empirically score agent task execution paths. Identifies drift, loop cycles, and error regressions before deployment.
SkillFortify
Adversarial prompt injection testing and payload filters specifically tuned for third-party tools and plugins.
SLM MCP Hub
Manages federated Model Context Protocol tools locally, with an average token-overhead reduction of 99.4%.
SLM Mesh
Coordinates cross-session signaling and shared state across multi-agent arrays.
Agent Amplifier
Five lifecycle hooks that amplify agent capability across the run loop — not just block it.
Research-backed, source-linked.
Every claim ships with a source. Nine public arXiv preprints, four of them on SuperLocalMemory alone.
Agent Behavioral Contracts II: Certifying Compositional Reliability Without Assuming Independence
AgentAssertSuperLocalMemory 4.0: The Governed Memory Operating System for AI Agents
SuperLocalMemoryQualixar OS: A Universal Operating System for AI Agent Orchestration
Qualixar OSSuperLocalMemory V3.3: The Living Brain -- Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems
SuperLocalMemorySuperLocalMemory V3: Information-Geometric Foundations for Zero-LLM Enterprise Agent Memory
SuperLocalMemoryAgentAssay: Token-Efficient Regression Testing for Non-Deterministic AI Agent Workflows
AgentAssayFormal Analysis and Supply Chain Security for Agentic AI Skills
SkillFortifyAgent Behavioral Contracts: Formal Specification and Runtime Enforcement for Reliable Autonomous AI Agents
AgentAssertSuperLocalMemory: Privacy-Preserving Multi-Agent Memory with Bayesian Trust Defense Against Memory Poisoning
SuperLocalMemoryWhat makes us different.
Open source by default
AGPL or Apache on every product. Read it, fork it, ship it. No "open source" with a tracking pixel.
Local-first
Memory, evals, telemetry — all on your machine. Your agents don't phone home unless you tell them to.
Zero cloud lock-in
Every product runs against any LLM provider, any vector store, any orchestrator. Swap freely.
Open research
Nine public arXiv preprints make the methods inspectable. Benchmark scope and release evidence stay explicit.
Join the AI Reliability Engineering movement.
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