We have multiple staff members report that the Hatz platform delivers noticeably slower response times compared to competing LLM platforms (ChatGPT, Claude.ai, Perplexity), with a key frustration being the visibility of verbose internal tool calls, reasoning chains, and processing steps that clutter the UI and delay perceived response time. This issue persists across multiple LLM models within the platform, indicating a systemic platform-level UI/rendering problem rather than a model-specific issue. We recommend optimizing response delivery to hide or defer tool calls and reasoning logic from the primary output stream by default, allowing users to see clean, actionable results immediately, with detailed reasoning available only on demand via an expandable section or user preference toggle.