Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
Auto Ontology is a Python framework for building semantic, graph-based reasoning layers over data. It enables deterministic query generation, better context retrieval, and more explainable AI for LLM and agent workflows.
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
NORDEF Matrix Open Control: model-independent AI safety belt with 0/1/2 decisions, Ed25519 root gate, replay protection, evidence chain, and incident-pattern eval bank
Cost-efficient coding-agent runtime: prefix-aware prompt-cache routing, poisoning-safe semantic cache, budgeted context compression, request batching/dedup, cascading model routing with DP-optimal policies, hard budget scheduling, span-level cost attribution, sandboxed tools, synthetic workload factory. NumPy core, CPU-only torch extra.
Offline voice-agent application layer: session core with byte-deterministic replay, spoken-LLM adapters (scripted/replay/loopback-mock), injection-safe function-call grammar, slot grounding, workflow engine with compensation and resume, permissioned tool sandbox, repair-dialog policies, task-success and latency evaluation. NumPy core, torch extra.
Refusal removal as a loadable KV-cache graft — zero weight modification, no refusal-direction projection, fully reversible.
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