AI
Reliability
Engineering
Qualixar is the research laboratory defining the specifications, constraints, and runtime meshes for autonomous intelligence networks.
The Qualixar Arsenal
Nine 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.
Bounded Loops
68 bounded agent-loop folders across 12 industries, 64 keyless out of the box, with independent gates and auditable receipts.
Peer-reviewed, not vibes-reviewed.
Every claim ships with a paper. Eight on arXiv as of May 2026, three of them on SuperLocalMemory alone.
Qualixar OS: A Universal Operating System for AI Agent Orchestration
Qualixar OSSuperLocalMemory V3.3: The Living Brain — Cognitive Memory for AI Agents
SuperLocalMemorySuperLocalMemory V3: Information-Geometric Agent Memory
SuperLocalMemoryAgentAssay: Token-Efficient Agent Evaluation via Stochastic Verdicts
AgentAssaySkillFortify: Securing the AI Agent Skill Supply Chain
SkillFortifyAgentAssert: Behavioral Contracts for AI Agent Compliance
AgentAssertSuperLocalMemory V2: Privacy-Preserving Multi-Agent Memory
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.
Peer-reviewed
Eight arXiv papers backing the claims. The benchmarks reproduce. The math is in the appendix.
Join the AI Reliability Engineering movement.
One email a week. New papers, new releases, the occasional war story from production. No fluff.
No spam. Unsubscribe in one click. ~1,200 engineers reading.