About GoProfy
Where GoProfy comes from
GoProfy is a product of CODHZ — a research and development company that builds proprietary reasoning systems for complex decision-making.
For over two decades, CODHZ has worked on a specific problem: how to make AI reason better, not just faster. Most AI tools process your question and return a pattern from their training data. CODHZ systems do something different — they apply structured reasoning protocols that determine what kind of thinking is valid for a given problem, in what sequence, and from what perspective. The intelligence lives in those protocols, not in the language model running underneath.
GoProfy is what happens when those protocols are applied to one of the most common and consequential questions a founder faces: Is this idea worth pursuing, and how do I move on it?
Built on something deeper than a prompt
There's a category of AI tools that connects a simple interface to a general-purpose model and calls the output "analysis." GoProfy is not that.
The analysis engine behind GoProfy runs on reasoning architectures developed by CODHZ — layered systems that process your business idea through multiple analytical lenses in sequence, each one reframing the output of the previous. The result is not a summary of what you wrote. It's a structured inference about what your inputs actually imply: where the gaps are, what forces are in play, what the most likely failure points are, and what specifically you should do first.
Part of a broader ecosystem
GoProfy is one of several products CODHZ has built on its core reasoning infrastructure.
JumPrompt
Takes a simple idea and architects it into a sophisticated, multi-layered prompt — built for people who want genuinely precise outputs from AI without becoming prompt engineers themselves.
AdvyBoard
Creates a personalized expert committee that meets with you in a virtual boardroom — a thinking environment designed for decisions that benefit from structured challenge, not just information retrieval.
Each product solves a different problem. All of them run on the same underlying commitment: that the quality of AI output is determined by the quality of the reasoning structure applied to it, not by access to the most powerful model.
What we believe
Most people interact with AI at the surface level — they ask, it answers. We build for the layer underneath: the logic that decides what counts as a valid answer, what gets weighted, what gets filtered, and in what order conclusions are reached.
That layer is harder to build. It takes longer. It can't be replicated by connecting to the same API everyone else is using. We think that's exactly why it's worth building.
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