Data-Review: PR Data Diff Tool

Teams using AI for code generation often don't validate the numerical outputs before merging. Data-Review lets developers diff and review the actual data/numbers changed in a PR, catching mistakes before they reach production. Target users: data teams, analytics engineers, and legacy industry companies adopting AI.

AI-assisted code generation is creating a genuine blind spot: developers reviewing diffs for logic correctness while numerical outputs go unvalidated, and this is showing up in production incidents at data-heavy companies right now as LLM adoption accelerates. The closest analogue is Great Expectations or dbt tests, but those are assertion frameworks requiring upfront schema knowledge — catching regressions in the review stage, before merge, is meaningfully different and largely unaddressed by existing tooling. The $500–3k/mo band is honest for a dev tool selling to analytics engineers and data teams at mid-sized companies, but it implies success depends on volume of seats or accounts rather than any single large contract, which is a slow grind. The real failure mode is that this lives in a workflow layer — PR review — where adoption requires changing team habits, and most data teams will reach for a dbt test or a quick Pandas assertion rather than add another tool to their CI pipeline.