OrgPulse AI: Design of a Bilingual Survey Platform for Weighted, Axis-Based Organizational Measurement

Organizations in the Arab world run employee and stakeholder surveys on tools that were built for English first. Arabic support in those tools is usually a translated interface on top of an English analytical pipeline, and the analysis itself tends to stop at raw response counts. This paper describes OrgPulse AI, a web platform I built to measure organizational health in Arabic and English through surveys structured around weighted thematic axes. The platform computes a deterministic set of metrics without any AI involvement: axis scores normalized to a 0-100 scale, top-box favorability, a consensus index derived from response dispersion, a worst-case margin of error, and an improvement priority ranking defined as axis weight multiplied by its performance gap. A second, optional layer adds inferential statistics on top of these descriptives: Welch's t-test for segment comparisons, normal-approximation confidence intervals, and Cronbach's alpha for axis-level internal consistency, all implemented from first principles and verified against reference values. Large language models sit outside this statistical core as a design and narration layer: GPT-4o drafts survey structures, questions, and weights during creation, and Claude Sonnet 4 writes executive narratives over the computed results. The paper also describes a portal mechanism that lets a parent organization share reports with subsidiary or client entities through PIN-gated pages, a pattern that matches how Saudi government bodies distribute assessment results to affiliated units. I state the platform's limitations plainly: the instrument is user-defined rather than psychometrically validated, scores aggregate at the question level rather than the respondent level, and the exploratory dialect-signal layer described in Section 5.2 has not been validated against human-coded ground truth. The contribution is an architectural and measurement pattern, documented from the actual implementation, for teams building survey analytics in languages that mainstream tools treat as an afterthought.