Cyntro Systems · Engineering
AI systems act. The interesting question is what keeps them in bounds. We build the layers that decide what an AI may install, change, remember and say – as running systems, not slides.
Everything on this page exists as running code. Part of it is open source – you can read it instead of taking our word.
A CLI gate that evaluates policy before npm, pnpm or bun run a single install script: release age, lifecycle scripts, non-registry sources, typo-squatting, Sigstore provenance and trust downgrades. Built for developers and AI coding agents – it hooks into Claude Code, Codex and Cursor at shell level and exposes an MCP server so agents can consult the policy before suggesting a package.
Vendor-neutral local mission control for AI coding agents: tasks, branches, worktrees, pull requests and deploy drift in one control plane. Built for repositories where several agents and humans work in parallel, and the question “who changed what, and is it merged?” must have exactly one true answer.
A shared memory substrate for AI agents: decisions, outcomes and open questions survive the end of a session and are readable by the next agent – vendor-independent. An AI librarian curates the memory instead of letting it rot. The system runs our own operations, every day.
Adaptive Context Perception Injection Protocol – a protocol that injects external context into live real-time AI sessions without interrupting the conversation. Two Austrian utility model applications are on file (GM 55087/2025, GM 50124/2026); an international (PCT) application is in preparation.
No sales layer. If you want to discuss protocols, agent infrastructure or a pilot, you reach the person who wrote the code.
office@cyntro.at