ZwischenZwischen is an inline adversarial review layer for AI agents — designed to challenge model outputs in real time, before they become actions, tickets, advice, or policy.
AI systems don't fail loudly — they fail plausibly. And when multiple models agree, it often means they learned the same shortcuts.
Zwischen introduces a deliberate interruption: a cross-model adversarial challenge that pressures a claim, exposes weak reasoning, and forces a harder standard before anything leaves your system.
Zwischen comes from zwischenzug — the chess "in-between move" that disrupts the expected line. Insert the unexpected challenge at the moment it matters.
We're opening early access to a small number of teams building agentic systems where mistakes are expensive.