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description=GitClear is a developer-friendly Software Engineering Intelligence platform that helps managers and developers digest code faster to exceed their performance KPIs. Upgrade your development with in-depth code analysis, DORA metrics benchmarks, enhanced Agile metrics, and AI assisted code review.;

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Text of the page (random words):
measure ai roi with research backed developer productivity metrics gitclear research learning signature features commit activity browser 30 slimmer pull requests snap changelogs ai powered visual change snapshots directory browser help center index developer experience top 7 gitclear benefits for devs 30 goals for healthy dev teams best software engineering metrics developer satisfaction survey tool diff delta correlation research tech debt measure and fix it manager corner encyclopedia of dev analytics 2025 2026 ai research annual performance reviews fast popular software engineering metrics and how they re gamed all research learning january 2026 research ai coding tools attract top performers but do they create them documentation security pricing blog log in sign up for vps of engineering for ctos and ops leaders know what your ai coding spend is actually returning gitclear pinpoints which lines of code came from copilot cursor claude code augment codex or gemini then scores durable output against rework duplication and defects one roi number your board can read get your ai roi scorecard free demo no credit card scorecard underway in 10 min soc 2 type ii ai code roi scorecard vantara generated apr 2026 last 90 days 14 contributors 01 ai tool adoption copilot 62 cursor 28 claude 19 02 weekly ai usage by developer weekly ai assisted commits 12 wk by developer low high 03 roi signals 41 ai attributed lines 22 durable change ai 79 devs using ai 30d 1 3 rework vs human ai quality research cited by the methodology one defensible number three inputs that can survive a board meeting inspired by google dora gitclear s ai roi score combines attribution output quality and developer experience so a single number holds up to scrutiny from finance the board and your own engineers 01 attribution which model wrote which line no more we think or estimated gitclear combines three signals to produce line level attribution with commit grade confidence ai usage apis commit heuristics agent telemetry hooks 02 output quality did the code actually survive diff delta quantifies durable change vs churn per author human authored and llm authored lines are measured side by side using the same yardstick diff delta rework rate duplication defect density 03 dev experience is the team better for it productivity gains are hollow if developers are drowning we fold in self reported time savings and satisfaction scores the space framework made actionable dev surveys self reported hours saved satisfaction 1 5 why dora as a starting point the same people who gave engineering leaders a defensible way to measure delivery in 2015 are now watching the ai transition closely gitclear s framework extends dora s four keys with the attribution layer dora doesn t attempt because commit level ai attribution didn t exist when dora was written how it works from three data sources to one number in about ten minutes connect your git host point gitclear at your ai vendor apis your first scorecard renders before the kickoff call ends ingest three sources unified gitclear pulls from your git provider your ai vendor usage apis and a lightweight agent telemetry hook no proxy no man in the middle github gitlab bitbucket azure devops claude code api or hook github copilot cursor augment codex gemini attribute line level authorship every line is tagged authored_by_llm with provenance which model which session which developer accepted it ambiguous lines get flagged not guessed authored_by_llm provenance ambiguity flag score scorecard dashboards a boardroom ready roi scorecard plus drill downs into durable change velocity ai hotspot directories and rollout readiness signals roi scorecard hotspot map cohort comparison vs the rest of the category most tools measure adoption gitclear measures whether the output is worth it linearb dx and jellyfish can tell you how many developers use ai none of them can tell you whether those developers are shipping durable code because none of them do line level attribution capability gitclear linearb dx jellyfish line level ai attribution yes pr level no no durable vs churned code scoring yes diff delta rework rate only no no human vs llm comparative outcomes yes no no aggregate only multi vendor ai usage api support claude code copilot cursor codex augment gemini yes copilot only yes free self serve tier yes dora only demo required demo required published longitudinal research 211m lines 3 yrs vendor claims survey based partner research the research moat the largest public study of ai s effect on code quality by a wide margin gitclear s ai copilot code quality report has been cited by mit technology review techcrunch and the new stack our competitors quote our findings in their own marketing we think you should get them from the source 211m lines of code analyzed across three longitudinal studies 2024 2025 2026 8 increase in duplicate code blocks since ai coding assistants became mainstream 9 higher code churn from ai power users producing 4 10x more code volume the numbers above are why this homepage exists ai has not made developers 50 more productive not in any codebase we ve measured and we ve measured more of them than anyone it has created a new class of risk code that ships faster than the team can reason about it gitclear s roi score is the one number that reflects both sides read 2026 ai reports pricing free until you want the scorecard connect your repos and get the full dashboard for free forever upgrade when you need the scorecard ai attribution apis or unlimited contributors free 0 up to 10 contributors diff delta velocity pr review insights basic dora metrics no support start free pro 14 95 dev mo unlimited contributors everything in free ai roi scorecard line level ai attribution claude copilot cursor codex augment gemini developer experience surveys priority support get the scorecard enterprise custom sso soc 2 on prem everything in pro self hosted deployment custom sla dedicated csm dora compliant reports get a free demo see what your ai spend is actually returning connect your repos get your scorecard in under ten minutes no credit card no sales call required unless you want one get your ai roi scorecard book a demo product ai velo code quality research ai code quality signal graphs changelog compare to dx compare to pluralsight flow compare to jellyfish compare to linearb diff delta mathematics encyclopedia of developer metrics open repos software engineering metrics company about best github alternative pr tool blog ensuring dev friendly metrics software metrics research github profile widget media press pricing security resources api 2025 ai code quality research dora in detail implementation engineering analytics tools compared feature voting board free git stats free code quality report dora gitclear ambassadors product reference documentation rich diff checker contact us code learn repeat see the latest blog post q2 2026 updates a data agent that answers anything claude telemetry without enterprise and six measured ai providers now on the internet 2026 gitclear all rights reserved privacy policy terms of use cookies policy gitclear uses cookies to ensure you get the best experience on our website learn more about our cookie policy