Hivel (hivel.ai)

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Cross-organization measurement of AI's realized effect on software engineering, joined to delivery outcomes. The AI Impact Analytics product links AI tool consumption (seats, tokens, credits, model usage) to measured outcomes - cycle time, rework, hotfix resolution, coding time and delivery health - and segments engineers into power, regular, occasional and inactive AI-user cohorts so the correlation between heavy AI use and faster, cleaner shipping can be tested directly. The SURGE framework structures this as Spend / Utilization / Recovery / Gain / Efficiency, i.e. whether an organization's system converts AI budget into output. Around it sits a broad engineering-telemetry surface: DORA delivery metrics, SPACE developer-experience metrics, pull-request review and merge cycles, coding hotspots, code churn and tech-debt quadranting, work-item detail, R&D cost visibility and capitalization for finance, plus team-health and burnout indicators. Historical cohort trends are retained since AI rollout, and a named enterprise reference (Freshworks) reports throughput, rework, feature-count and time-to-market outcomes.