The Challenge

AI agents can perform complex work, but their users still spend time repeating preferences, rebuilding project context and correcting the same mistakes. Decisions are scattered across conversations and tools, making it harder to switch agents or resume work consistently. Instruction files and built-in memory help, but keeping them current across projects and providers takes effort. Developers and independent founders need a practical way to carry their decisions and standards into each task, while retaining control over their data and the choices that require their judgement.

The solution

Varyz gives connected AI agents a shared source of personal preferences, project decisions and relevant work history. It briefs agents before work starts, answers from settled decisions, queues new questions during away mode and supplies completion checklists. This coordinates how agents work across tools while the user retains control. The working prototype integrates with Claude Code, Codex and Cursor; private Cloud retrieval supports separately approved history. The planned business model combines free local software with optional paid Cloud access across devices and connected tools. Public launch is being prepared; business and enterprise offerings are future opportunities.

Mission

Help people get more done with AI by carrying their experience, decisions and standards into every task.