Jellyfish

JELLYFISHA5 · direct accessManage supplier listing

Cross-enterprise AI coding-tool adoption and delivery-outcome telemetry spanning more than 1,000 companies. Adoption side: access percentage (engineers holding a licence), frequent-user percentage (three or more days per week), cohort-level adoption by team, role and rollout phase, and time to first AI-assisted merged commit. Output side: share of merged code that is AI-assisted, pull-request throughput, cycle time, change failure rate, time to merge, plus spend by tool and by team. Published aggregate reference points: median AI adoption 74% against median AI-assisted code 27%. Coverage spans Copilot, Cursor, Claude Code and agentic tools, reconciled from vendor admin-console access data against Git history at team and repository level, with quarterly developer-experience sentiment surveys layered on top.

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Coverage

Universe, instruments and categories.

Industry: Application Software
Instruments: equities
Categories: AlternativeSentimentFundamental
Regions: US
Sample tickers: MSFTGITHUBNETMDBSNOWDOCUHUBSWTWPANWZS

Dataset card

Type: not stated
Format: Tabular telemetry time series (per-engineer, per-tool adoption events; per-repository and per-team commit and pull-request records with AI-assistance attribution; cycle-time, throughput and change-failure series; spend by tool and team) + quarterly survey sentiment series + executive report aggregates
Volume: Order 10^7-10^8 commit and pull-request records with AI-assistance attribution across 1,000+ companies (inferred: engineering organisations of 50-5,000 developers x 10^2-10^3 changes per developer per year), plus per-engineer per-tool adoption events across Copilot, Cursor, Claude Code and agentic tools
Users: 1,000+ companies on the platform (stated on the page), implying engineer-level coverage in the low-to-mid hundreds of thousands across the customer base (inferred from a $31.9M revenue range and 230 employees against enterprise engineering-management ACV)
History: 6 years
Update frequency: not stated
Growth: Active and expanding into AI measurement - current-dated 2026 publications, a dedicated AI Impact product line and a published AI engineering trends series, with sustained venture backing at Series C and $117.2M raised
Launched: ~2016-2017 for the core engineering-management platform (inferred: a Series C with $117.2M raised and 230 employees implies roughly a decade of operating history; the AI Impact layer is a 2024-2026 addition bounded below by the general availability of the AI coding tools it measures). No founding year printed on the page
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

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