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Comparison · HR
Factorial HR vs Ever Gauzy
A side-by-side editorial comparison of Factorial HR and Ever Gauzy — release velocity, themes, recent moves, and the top alternatives to consider.
Factorial HR vs Ever Gauzy: at a glance
What is Factorial HR?
Factorial's API ships quarterly versions, and added an MCP server and SDKs this summer.
Factorial's developer changelog follows dated API versions: 2026-04-01, 2026-07-01 and 2026-10-01 have shipped, and 2027-01-01 release notes are already posted. In July it added an MCP server and official TypeScript and Python SDKs with a skill for AI coding agents. The version entries carry no detail in this feed.
What is Ever Gauzy?
Ever Gauzy links time logs to invoice lines so the same hours are never billed twice.
Ever Gauzy ships many small tags a day, most built and reviewed with AI code-review bots. November 13 alone brought seven tags: invoice lines now record the time logs they bill, with a filter that leaves out time already invoiced, chat suggests team names for new channels, and task automations react when a linked GitHub pull request or issue closes. The rest are fixes for date-only due dates, chat on Postgres and MySQL collations.
Factorial HR vs Ever Gauzy: editorial side-by-side
Factorial's API ships quarterly versions, and added an MCP server and SDKs this summer.
◆ Current state
Factorial's developer changelog follows dated API versions: 2026-04-01, 2026-07-01 and 2026-10-01 have shipped, and 2027-01-01 release notes are already posted. In July it added an MCP server and official TypeScript and Python SDKs with a skill for AI coding agents. The version entries carry no detail in this feed.
◆ Where it's heading
The API is on a predictable quarterly release train with notes published a quarter ahead, which suits integrators planning upgrades. The July MCP server and agent skill show Factorial treating AI assistants and coding agents as API consumers alongside classic integrations.
◆ Prediction
The 2027-01-01 API version is the next likely release, around the start of January, given the posted notes and quarterly pattern.
Ever Gauzy links time logs to invoice lines so the same hours are never billed twice.
◆ Current state
Ever Gauzy ships many small tags a day, most built and reviewed with AI code-review bots. November 13 alone brought seven tags: invoice lines now record the time logs they bill, with a filter that leaves out time already invoiced, chat suggests team names for new channels, and task automations react when a linked GitHub pull request or issue closes. The rest are fixes for date-only due dates, chat on Postgres and MySQL collations.
◆ Where it's heading
The platform is tying its separate modules together: time tracking to invoicing, chat to teams, and tasks to GitHub events. The fast tag cadence means each feature arrives with several follow-up fix tags the same day.
◆ Prediction
Expect more task-automation triggers from external tools after the GitHub closed-link event, and invoicing work that uses the new billed-time links.
Alternatives to Factorial HR and Ever Gauzy
Other HR products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Factorial HR or Ever Gauzy.
Leapsome
Leapsome publishes another batch of HR templates and software roundups.
Ashby
Ashby adds threaded comments to AI Notetaker, so interview debriefs stay next to the transcript.
Teamtailor
Teamtailor shows every time in the reader's own time zone, for recruiters and candidates.
Workable
Workable turns its report builder on interviews, assessments and video screens.
Fountain
Fountain opens a skills marketplace for its Cue assistant and adds a compliance review queue.
See all Factorial HR alternatives → · See all Ever Gauzy alternatives →
Recent activity from Factorial HR and Ever Gauzy
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 18h agoEver Gauzy111.211.0: task rules react to closed GitHub PRs and issues
- 19h agoEver Gauzy111.210.3: bulk task changes use the org's own status records
- 20h agoEver Gauzy111.210.2: chat collation fixes on MySQL and MariaDB
- 23h agoEver Gauzy111.210.1: date-only due dates fall on their own day
- 1d agoEver Gauzy111.210.0: invoices record the time logs they bill
- 1d agoEver Gauzy111.209.4: API boots with chat on Postgres again
- 1mo agoFactorial HRFactorial API version 2026-10-01 goes live
- 1mo agoFactorial HRFactorial posts notes for its 2027-01-01 API version
- 4mo agoFactorial HRIntroducing the Factorial MCP server
- 4mo agoFactorial HROfficial TypeScript and Python SDKs — plus a skill for AI coding agents
- 4mo agoFactorial HRFactorial API version 2026-07-01 goes live
- 4mo agoFactorial HRFactorial posts notes for its 2026-10-01 API version
Frequently asked questions
What is the difference between Factorial HR and Ever Gauzy?
They serve adjacent needs but don't currently overlap on shipped themes. Ever Gauzy is currently shipping more aggressively (velocity 7.5 vs 2.5), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Factorial HR better than Ever Gauzy?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Ever Gauzy is currently shipping more aggressively (velocity 7.5 vs 2.5), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other HR products to evaluate alongside.
What are the best alternatives to Factorial HR?
Top Factorial HR alternatives in HR are ranked by recent ship velocity. Browse the "Factorial HR alternatives" section above for the current picks, or visit /alternatives/factorial-hr for the full list with editorial commentary on each.
What are the best alternatives to Ever Gauzy?
Top Ever Gauzy alternatives in HR are ranked by recent ship velocity. Browse the "Ever Gauzy alternatives" section above for the current picks, or visit /alternatives/ever-gauzy for the full list with editorial commentary on each.